My my main interests involve social systems informatics. The this interdisciplinary program in Social Systems Informatics is directed towards advancing and disseminating computational approaches involving the measurement, modeling, and testing of how social interactions affect a broad range of human outcomes. These social interactions range from face-to-face, media communications, or other social actions and are often massive in size. Key outcomes involve major characteristics of our lives related to education, health, work, and play; attitudes, behaviors, performances in these areas are not simply products of individual factors but are fundamentally shaped by the social contexts and interactions in which people live. Computationally, social systems informatics relies on methods in system science, including social network analysis, agent based modeling, data mining, intelligent data analysis, and biostatistical methods, to study how individual and social system interactions affect health and other outcomes.

Smart Visualization: One picture is worth a thousand words. For thousands of years, people have been using information graphics—visual representation of data—to comprehend and analyze information. However, creating high-quality visualization is a daunting task especially for ordinary people who are neither graphic artists nor computer scientists. To democratize the use of visualization, I am interested in automated visualization design and tailoring the visual responses to highly dynamic user interaction situations and unanticipated information. More recently, I have been working in the area of interactive visual text analytics, which combines state-of-the-art text analytics with novel interactive visualization to empower average business users to analyze massive amounts of textual data and facilitate their decision making (e.g., making a purchase decision based on the visual text analysis of extensive consumer reviews).

Mixed-initiative Human-Computer Interaction (HCI): I believe that the future of HCI is to facilitate the development of a man-computer symbiosis where both humans and machines can leverage their strengths and avoid their weaknesses. I am especially interested in the development of mixed-initiative intelligent information systems, where the humans and computers work together collaboratively to facilitate information seeking an analysis. To enable computers to take sensible initiatives and push this class of systems to main stream applications, I am particularly interested in developing novel and practical computational approaches to the problem. Moreover, I am interested in exploring new interaction paradigms where users can interact with complex system responses (e.g., system-derived text summarization results) and the use of interactive machine learning in support of an adaptive, mixed-initiative human-computer interaction, where both humans and computers can learn from each other.

Opportunistic Social Computing: The use of social software (e.g., social networking, micro-blogging, and online forums) has penetrated the masses. I am very much interested in finding out how such phenomena will change our daily lives as well as its long-term impact on our world. In particular, I am especially interested in how social computing will bring us opportunistic information and collaboration partners whenever we need them but without subjecting ourselves to “constant availability and instant intimacy” as we do today. To achieve this goal, I believe there are fundamental research issues to be addressed.They include but not limited to:

•Understanding, modeling, and automatically deriving social profile of a person, a community, or an organization based on their digital footprints (i.e., online behavior);
•Use of the derived social profiles to objectively reveal key characters of individuals and organizations, assess community/organization dynamics, value, and risks, predict the development or growth of individuals, communities and organizations, and help establish opportunistic collaborations among individuals and organizations;
•Monitoring social channels (e.g., facebook and twitter) and detecting most valuable channel(s) for extracting social intelligence (e.g., knowledge about car repair or the consumer complains/needs); Mining of social messages to distill insight (information or people) for opportunistic information sharing (e.g., sharing the extracted consumer complains), knowledge acquisition (e.g., asking target audience to voice their problems and suggest their solutions), and crowd-sourced problem solving (e.g., social Q&A). See my webpage for more info.

The Computer Supported Collaboration (CSC) Laboratory conducts research to inform the design of information systems for collaboration.

We investigate the development and use of information infrastructures in science and engineering, computer supported cooperative work (CSCW), and computer supported cooperative leisure. Recent projects have explored these themes in domains like environmental microbiology, functional brain imaging, museum exhibit design, and online calendar sharing. Previous exposure to CSCW research and some interest in biological and physical science is desirable for this position.

We use primarily qualitative social science research methods, often conducting interviews or observational fieldwork in places of work and leisure to holistically investigate information systems as evolving social and technical entities. Candidates should have familiarity with literature on to the topics of cyberinfrastructure or boundary objects and independent research experience using qualitative social science methods.

The focus of my research is information seeking and behavior that goes beyond individuals. Specifically, I am interested in information seeking activities that take place in groups/collaboration, or in online communities using various social media or networking services. My primary objective for studying these topics is to develop a theoretical framework for investigating information seeking and behavior involving multiple actors/participants and their interactions that is lacking for collaborative and social situations. Another related objective is to build a model for evaluating and explaining various aspects of information propagation through interactions among people whether they are working in close collaboration or connected through open online communities. This direction leads to investigations related to “information as a thing” and construction of online communities around information seeking and sharing. A by-product of such investigations would be their applications to analyzing various socio-political issues through social media usage and user participation.

At Rutgers, I run a research group on information seeking (http://www.infoseeking.org), with subgroups on collaborative information seeking (http://collab.infoseeking.org) and social information seeking (http://social.infoseeking.org). I’m also associated with the social media group (http://sm.rutgers.edu) and the NLP group (http://salts.rutgers.edu).

HP Labs Immersive 3D

HP Labs is conducting research using large display walls, 2D and 3D. HP has multiple product and services offerings in the so-called “Big Walls” area ranging from digital signage to large telepresence facilities (such as HP’s Halo). Our research extends this by following two main, intertwined branches. The first examines a new style of 3D entertainment, and the other targets commercial and industrial uses for 3D enabled operations centers, brainstorm or war rooms, and control centers. We are conducting research in:
• Computer vision, image processing, and recognition,
• Robust multi-imager and multi-camera modeling and calibration,
• 3D data visualization,
• High performance computation, transport, and imaging on hardware accelerated platforms (CPUs and/or GPUs),
• Novel human-big wall interaction modalities across heterogenous systems, and
• Local and remote collaboration technologies.

We have publicly shown our Immersive 3D Entertainment efforts with events at the 2010 Sundance Film Festival and the Earth Wind and Fire Concert at 2011 CES in Las Vegas (links listed below). HP’s goal is to experiment with non-standard aspect ratios (e.g. 3:1 for concert stage, 5.5:1 for basketball court) to allow the audience to experience the event as though you are seated at the best seat in the house. This is a break from the traditional movie view from the director’s eyes and allows the audience to “look around” and soak up the scene which works so well in 3D. To do this, we are experimenting with large multi-projector 3D displays (Pluribus), multi-imager camera capture (Herodion), and advanced digital image pipelines (Pericles). We conduct in-situ laboratory studies at entertainment events such as concerts, sports events, fashion shows, and other gaming.

We have built an experimental operations center with multiple 2D and 3D walls and other services. Together with many HP customers, we are exploring novel ways to use Big Walls to address issues in areas such as disaster recovery, emergency response, hospital wards, city monitoring and management, mergers and acquisition planning, product planning, and supply chain management. We are creating a next generation capability by using Big Walls together with mobile devices, touch surfaces, 3D data visualization techniques, and techniques for displaying, manipulating and visualizing large amounts of unstructured data. In addition to our research, we participate in the real world by providing support for HP’s worldwide operations centers and the HP supported gallery at the Newseum due to open in 2012.

Links to entertainment reviews
HP 3D Live: CES Earth Wind and Fire concert

http://blogs.forbes.com/oliverchiang/2011/01/08/ces-hp-believes-in-3-d-too-but-on-a-larger-scale-much-larger/

http://www.monstercable.com/events/ces2011/3dexperience.asp

http://h20435.www2.hp.com/t5/The-Next-Bench-Blog/Earth-Wind-and-Fire-Going-Large-Live-and-in-3D-at-CES/ba-p/60745

http://www.hardwaregeeks.com/index.php/site/comments/hp_streams_concert_live_in_3d/

http://venturebeat.com/2011/01/14/hp-streams-earth-wind-fire-in-live-3d-on-a-huge-screen/

2010 Sundance Film Festival

http://philmckinney.com/archives/2010/01/sundance-and-3d.html

http://h20435.www2.hp.com/t5/The-Next-Bench-Blog/Stories-in-3D/ba-p/52743

HP Newseum announcements

http://www.hp.com/hpinfo/newsroom/press/2010/100930a.html

http://www.newseum.org/news/2010/09/hp-announcement.html

Design, implementation and evaluation of distributed services and applications that adapt and exploit social characteristics; algorithms for efficient computation of social graph metrics (e.g., centrality measures, triad census); experimental systems approach combined with theoretical and analytical evaluations.

I work mostly in two areas Computational Geometry and Computational Biology.

I have broad HCI and CSCW interests. I am interested in cognitive/social design principles underlying the design of systems in the following areas:
- large scale social and collaborative systems (e.g. communities)
- personal information management
- digital support for memory/lifelogging
- interactive information retrieval

My university is just 5 mins from the Pacific in a beautiful part of n. California

I am broadly interested in the area of data mining, machine learning and Information retrieval in application areas such as Bioinformatics, E-Commerce and Social Sciences. In data mining, I worked on generic pattern mining, graph mining, clustering, and nearest-neighbor query. In Bioinformatics, I worked on protein docking and currently working on subgraph mining from PPI networks. In e-commerce, I have worked on query suggestions and query segmentation. In information retrieval area, I have worked on ranking of patent documents. My doctoral thesis on subgraph sampling got ACM SIGKDD dissertation award in 2010.

I do work research in social computing and social media. My approach to research typically centers around using computational methods (e.g., applied NLP) to both understand the social internet and build new systems for it.

Current topics:

* Building new email interactions
* Building new interaction techniques for social networking sites
* Analyzing diffusion through networks over long spans of time
* Analyzing online social behavior through theoretical lenses

My work i is broadly at the intersection of HCI and Information Retrieval/Data Mining. I generally work with extremely large datasets of text (Web, large collections of scientific texts, historical collections of books), behavior (click and search logs), and networks (social systems, Web, P2P, etc.). My work tends to have both an empirical descriptive/modeling component as well as a system-building component (leveraging what know to build better systems). Current areas of focus include:

- Temporal-informatics – providing front ends to users who have data-extraction needs for time-varying data (e.g., http://www.cond.org/zoetrope.html)

- Meme mutation – how information mutates as it moves through networks

- Scientific data evolution – mining large collections of scientific literature to detect evolution and emergence

- Collaborative analytics/visualization – building systems to support users without a great deal of statistical and visual literacy in understanding data

- Privacy – how perceptions shape behavior

My research focuses on culturally appropriate uses of information and communications technology (ICT) to improve delivery of health information and health services in low-income countries. ICT offers many benefits, including access to online resources, electronic data collection, electronic storage and retrieval of patient data, etc. However, there may be social and cultural barriers to acceptance of the technology. Age, gender, class, education level, national or regional culture, level of urbanization, and political climate can all be potential barriers to acceptance. Careful understanding of social and cultural contexts is needed to avert such unintended negative effects. My research evaluates the acceptability and impact of handheld computers, mobile phones, websites, and other ICT in order to understand the social and cultural barriers to accepting ICT in healthcare settings in low-income countries.

My research builds on years of experience working with global health projects in sub-Saharan Africa. Currently, I supervise a program in Rwanda that offers medical and psychosocial care in two hospitals and four clinics throughout the country. I am also on the advisory board of a women’s health website with global reach.

The primary focus of our lab is understanding the work practices of IT professionals to inform the design of improved computational support. As such we have engaged a wide range of domains including healthcare, aerospace, network security, public education and online community management. We take a sociotechnical perspective and engage the full life cycle of research projects, from ethnographically-informed fieldwork through systems development, deployment and evaluation. We are currently engaged with a multi-faceted empirical investigation of the processes virtual organizing, especially with regard to virtual worlds and alternate reality games.

My research primarily focuses on enabling synergetic autonomy in human-robot interactions in dynamic real-world application domains such as elderly care and surveillance. Each robot operates autonomously as far as possible, using algorithms to: learn environmental models based on sensory inputs; adapt the learned models in response to environmental changes; tailor sensing and information processing to the task at hand; and robustly merge the information obtained from teammates. At the same time, the robot acquires and fully utilizes limited high-level information from humans through a variety of interaction modalities, e.g., vision, natural language and touch-screen visual displays.

I am also interested in designing and adapting Bayesian reasoning algorithms to address real-world challenges characterized by a significant amount of uncertainty. Some (current) examples of applications are: medical data processing, HRI/HCI interface design, and adaptive learning technologies for training teachers and promoting learning among students with disabilities.

The Interface Ecology Lab imagines and develops integral and sensitive human-centered computing to support nuanced and exciting aspects of life, including how we form and express ideas and intentions, how we learn and innovate, how we gesture and communicate, how we coordinate and cooperate, how we participate and share, how we function under stress, and how we respond to crises. We connect diverse methodologies, engaging an interface ecosystems approach to engage computing in holistic avenues of human experience.

We have just developed an innovative multi-finger sensor, ZeroTouch. We are now poised to integrate ZeroTouch into interactive environments, developing new embodied bi-manual and free air interaction techniques and experiences.

We have released the open source meta-metadata language and architecture, for authoring platform-independent wrappers for heterogeneous information sources. Meta-metadata supports information extraction and knowledge integration. It facilitates writing programs that enable new human experiences of information visualization, physically-based modeling, and embodied interaction. Research here involves new knowledge semantics and modeling, on the one hand, and new interactive visual applications, on the other. Social media and digital libraries are connected.

We are developing special relationships with disaster response organizations. Texas Task Force 1 engages in major disasters, such as 9/11, and hurricanes Katrina, Rita, and Ike. TEEX Disaster Preparedness and Response runs an internationally-renowned academy for first responders. We are engaged both in developing zero fidelity simulation games for education, and in creating innovative multi-surface information systems for crisis response.

The typical search interface is great for finding a single element of information, but weak for information-based ideation tasks, in which the human goal is to to develop ideas with support and stimulus from information. The combinFormation platform reconceptualizes information-based ideation support as mixed-initiative information composition, integrating browse-search-collect-visualize-and-organize, while representing each collection as a connected whole. To validate composition, information-based ideation metrics and grounded theory are extended and synthesized, developing formative and summative evaluation methodologies. Application contexts include thesis writing in computer science, and design in architecture and mechanical engineering.

I work to understand motion and change in video — separating changes in seasons from changes over a day in outdoor time-lapse, capturing the motion patterns in an MRI video of a heart, or parsing the surveillance video of a intersection into traffic cycles. I mostly work on data-driven methods that could scale to work with (for example) all the webcams connected to the web, or within large scale, image based Citizen Science applications.

There are several potential research projects within the linqs group at UMD (www.cs.umd.edu/linqs) ranging from core machine learning and probabilistic modeling, to applications in social network, personalized medicine and information alignment. We have a large research group and a CI Fellow would gain experience in mentoring undergraduate and graduate students, grant writing, and teaching (if interested).

The research goal of the Music Computation and Cognition group at USC is to systematically study, computationally model, and scientifically explain human abilities in music perception and cognition, and in music making, such as music performance, improvisation, and composition.

Research projects at the laboratory address the three main areas of music analysis, performance, and composition/improvisation. They include:

• decoding and generation of decisions and gestures in music performance;
• analysis of musical ensemble in networked music performances;
• multi-modal interaction in human-machine musical improvisation; and,
• automatic analysis and visualization of musical structure.

The MuCoaCo website — http://www-bcf.usc.edu/~mucoaco — and the MuCoaCo blog — http://mucoaco.blogspot.com — contain detailed project descriptions, video demonstrations, and lists of publications and awards. The broad areas spanned by the research projects are mirrored in the seminar course on Topics in Engineering Approaches to Music Cognition — http://www-scf.usc.edu/~ise575 .

The successful postdoctoral researcher is expected to engage in music computing research, and to have completed graduate-level training in at least one of the following quantitative analysis areas: mathematics, computer science, operations research, signal processing, statistics, or neuroscience. It is highly advantageous for the candidate to possess graduate-equivalent practical or theoretical knowledge in music analysis, performance, composition, or music perception and cognition. Preference is given to individuals with prior experience in music computing research.

MuCoaCo affiliates have had backgrounds in Computer Science, Electrical Engineering, Industrial and Systems Engineering, Music Composition, Music Performance, Neuroscience, and Psychology.

The Linguistic and Assistive Technologies Laboratory (LATLab) at The City University of New York (CUNY), Queens College, conducts research in computational linguistics and human-computer interaction with a primary focus on accessibility applications and assistive technology for people with disabilities. In particular, we study the design of computer technology to address language and literacy impairments of people with disabilities – with a focus on two groups: people who have intellectual disabilities (ID) and people who are deaf.

Animations of American Sign Language for People who are Deaf:

Our research at CUNY has focused on sign language animation technologies for people who are deaf. American Sign Language (ASL) is a primary means of communication for one-half million people in the U.S, and it is a distinct language from English – with its own unique word-order, grammar, and vocabulary. A majority of deaf high school graduates in the U.S. have only a fourth-grade English reading level or below, yet many of these adults have sophisticated fluency in ASL. Therefore, software that can present information in the form of ASL animations would improve these individuals’ access to websites, communication, and information. Using our motion-capture recording studio, we are collecting a corpus of ASL performances, linguistically annotating them (with the help of a team of native ASL signers), and analyzing this data to create models to underlie ASL animation technologies (to make them more natural-moving and understandable for deaf viewers). We conduct experimental studies at the laboratory on a regular basis in which native ASL signers evaluate animations synthesized using alternative models. We have studies models of speed/timing, use of signing space, verb inflection, and we are beginning a project on facial expression in ASL. We are also interested in issues relating to linguistic generation of ASL and English-to-ASL machine translation. Further, we are interested in studying other forms of signing communication, including various forms of Signed English used by people who are deaf or hard-of-hearing in the U.S.

Text Readability Detection / Text Simplification for People with Intellectual Disabilities:

Many people with ID have limited English literacy and could benefit from software that could help them automatically identify information sources or websites that are at an appropriate level of difficulty or that could automatically simplify complex texts. Based on linguistic features of a text that can be automatically calculated through NLP software (the part-of-speech of different words, the syntactic parse-tree of the sentences, etc.), we are designing software to assign a difficulty score to a text to indicate whether it would be accessible for an adult with ID to read. We are also experimenting with various experimental designs to gather ground-truth data about how difficult-to-read texts are for these users; this is non-trivial because it can be difficult for these users to participate in a traditional comprehension experiments.

Other Projects:

We are interested in other projects related to applications of computational linguistics or human computer interaction to accessibility or assistive technology for people with disabilities.

My primary research interests lie at the intersection of privacy, security, data analysis, and data management. I am very interested in the field of secure information sharing and its various applications; as also the application of secure computation technologies to business processes such as supply chain management and optimization. Our lab looks at different aspects of privacy, such as privacy in graph structured data, privacy in location based services, medical health record privacy etc. We are also interested in the use of data mining techniques to enhance security, such as in Role Engineering. As such, our lab looks at fundamental data mining problems such as boolean matrix factorization and the use of these for solving domain issues such as those in access control.

Please visit my webpage for more information.

Noshir Contractor (http://nosh.northwestern.edu) is the Jane S. & William J. White Professor of Behavioral Sciences in the McCormick School of Engineering & Applied Science, the School of Communication and the Kellogg School of Management at Northwestern University, USA. He is the Director of the Science of Networks in Communities (SONIC) Research Group at Northwestern University.

Professor Contractor is investigating factors that lead to the formation, maintenance, and dissolution of dynamically linked social and knowledge networks in a wide variety of contexts including communities of practice in business, translational science and engineering communities, public health networks and virtual worlds.

Research in the SONIC (Science of Networks in Communities) http://sonic.northwestern.edu which he directs seeks to understand and enable multidimensional social networks. Multidimensional networks include different types of nodes (such as people, documents, data sets, and tags) and the different types of relations that connect them.

In order to understand the emergence and dynamics of multidimensional social networks, research in the SONIC lab combines (social science) theory driven and data driven (statistically modeling, data mining and machine learning) approaches.

In particular the lab is interested in the statistical modeling of networks using p* /Exponential Random Graph Modeling (ERGM) techniques and stochastic actor orient modeling techniques (implemented in SIENA). In addition, there is a strong emphasis on conducting these analysis on large scale networks. The lab has access to many large scale server-side sources of data such MMOs (Massively Multiplayer Online games) and the Web of Science. The insights gained from understanding the emergence and dynamics of multidimensional networks is used to enable networks by building sophisticated recommender systems that provide individualized suggestions on who to collaborate with or what team to assemble.

His research program has been funded continuously for over 15 years by major grants from the U.S. National Science Foundation with additional current funding from the U.S. National Institutes of Health (NIH), Air Force Research Lab, Army Research Institute, Army Research Laboratory and the MacArthur Foundation.

Professor Contractor has published or presented over 250 research papers dealing with communicating and organizing. His book titled Theories of Communication Networks (co-authored with Professor Peter Monge and published by Oxford University Press, and translated into simplified Chinese in 2009) received the 2003 Book of the Year award from the Organizational Communication Division of the National Communication Association. He is the lead developer of C-IKNOW (Cyberinfrastructure for Inquiring Knowledge Networks On the Web), a socio-technical environment to understand and enable networks among communities, as well as Blanche, a software environment to simulate the dynamics of social networks.

I have broad research interests covering the impact of technology on work, social interactions and economics. As a user experience researcher, my specific interests include the design of knowledge management systems and online communities, secure mobile applications, workflow orchestration, and business process modeling by non-programmers.

My research group focuses on developing representations and algorithms for learning causal models of complex systems of interacting components. These can be human communities (e.g., scientific communities, corporations, and government agencies), online social networks (Facebook, LinkedIn, and Twitter), peer production systems (Wikipedia, Stack Overflow), and complex computer systems (data centers, multiagent systems). We are developing radically new methods that assist human investigators in understanding the deep causal structure of these systems.

Research in my group deals with various aspects of the Web and increasingly the social Web, or Web 2.0. This includes analyzing and modeling the diffusion of information in social media, and building better applications for Web search, recommendation, navigation, and annotation. We study crowdsourcing applications and their incentives, such as games and services with purpose, to leverage the wisdom of the crowds for social computing tasks. Finally we study collaborative and distributed approaches to make the social Web less susceptible to abuses such as spam and manipulation.

At the technology, open organizing, & learning sciences laboratory (toolsLAB) we examine how digital tools afford new ways of reorganizing knowledge sharing and knowledge building and impact learning and work practices. Through a fundamental understanding of the change occurring within the workplace and learning envirnments, we aim to design tools and technologies that can support creativity and innovation. Our current projects are looking at the use of Tablet PCs in engineering design, the use Wiki-based platforms for student advising, social network analysis of research collaborations, and learning practices in open source communities. Another major thrust of our lab is examination of communication and collaboration in virtual and globally distributed teams. This position will provide experience with field studies, technology development, and an opportunity to shape the education of future engineers.

Additional areas of interest: ICT for development, design for social empowerment.

Crowdsourcing, human computation, and collective intelligence are having profound implications for computing, posing many tantalizing research questions. Not only does the topic provide fertile land for research, it is also a topic where the time frame of a CI Fellowship can permit results with the significance and recognition that can help propel a career forward.

As one example direction, we now face micro-labor markets such as Amazon Mechanical Turk that allow us to write algorithms whose “subroutines” are people performing tasks at pennies a shot. How do we program this kind of “social computer”? What are the crowdsourcing analogs to the programming languages and IDEs that we rely on in traditional programming? I’m particularly (but not solely) interested in the role that machine learning can play here. For example, what’s the right way to do classification learning for problems that no longer need to assume that obtaining human labels on data is excessively costly, where people are now instead cheap albeit unreliable or differently motivated? This area not only poses new questions but also offers answers of relevance not just to the computational but also the behavioral sciences.

usability, creativity, design methods, participatory design, design rationale, community networks, mobile community networks, online community, virtual organizations, common ground, social capital, awareness, activity awareness, case-based learning,

My primary research interest is in the study of large-scale complex networks (such as technological, informational, and social networks) in order to build predictive models of such systems. Problems of interest span from knowledge representation issues to network classification and clustering, to attribution of macro-level behavior to micro-level elements. For more information, visit http://eliassi.org/pubs.html.

Our lab looks at the design and analysis of security and privacy mechanisms for Internet-scale systems. Some of our major thrusts are scalable systems for anonymous communication and analysis of encrypted traffic and its impact on privacy and security, and the protection of privacy in social networks. We are also looking at security and privacy issues in emerging applications, such smart phones, smart buildings, and smart grids.

Please visit my web page for more information about our research.

My research and educational career straddles the border between computational theory and mechatronic engineering. Motivated by applications in confined spaces, my group pursues a comprehensive program in mechanism design, path planning, motion planning, and estimation. These research topics are important because once the robot is built (design), it must decide where to go (path planning), determine how to get there (motion planning), and use feedback to close the loop (estimation). Already, we have directly applied this body of work to challenging and strategically significant problems in diverse areas such as surgery, manufacturing, infrastructure inspection, and search and rescue.

Many of the research fundamentals support the development of snake robots, highly articulated mechanisms that can thread through tightly packed spaces reaching locations that people and conventional machinery otherwise cannot. We have developed snake robots for minimally invasive cardiac surgery; recently, we completed our first in human procedure. Current work includes further mechanism development for natural orifice surgery, and prescribing estimation/filtering approaches, based on Kalman and Bayes filtering, to map the internals of the body, i.e., it is SLAM on the inside.

We are also addressing the motion planning of snake robots and all underactuated systems. Our approach takes recourse to the fundamentals, drawing from advanced concepts in differential geometry to prescribe gaits. Examples of results in this work are applying Stokes Theorem to the local form of the connection on shape spaces to efficiently design gaits. Recently, we have shown that many biological systems, including fish and lizards, can be modeled this way.

By taking recourse to the fundamentals, we have been able to address other problems such as multi-agent planning. Recently, we have developed an efficient provably complete optimal multi-agent path planner that can plan paths for 40+ robots in large spaces (note that the size of the configuration space makes it impossible for A* to even search one step, let alone complete a path). We have also developed an algorithm for multi-agent manipulation. Current work includes applying these techniques to distributed manufacturing. We are also working with a biologist to use these concepts to model swarms.

It is the excitement of working with students that continues to draw me to academia. I am certain that a casual tour of my lab reveals a feeling of energy and productivity. My students, both graduate and undergraduate, work hard to provide fresh new insights within the framework of mathematical and experimental rigor endowed by my research program.

Information assurance, cybersecurity, social networking

This is a general invitation on behalf of the Information Systems Research Community at NJIT. We have a large variety of NSF-funded and other research projects in HCC and III (human-centered computing / information integration & informatics) topics. Details are on individual faculty pages, accessible through http://is.njit.edu/people/faculty.php – see the research keywords listed here and on the faculty pages.

I’m interested in advancing the state of the art in developing environments that combine data management, computation, and collaboration to reduce the barriers to use of large-scale resources and to enable cross-disciplinary research and industrial design integrating heterogeneous data and models. I am looking for individuals interested in research coupled with application in support of scientific research, engineering design, or education; we have a number of projects involving collaborations with domain researchers in science, engineering, and the humanties that could provide concrete requirements and interested user communities for individual research topics.

1. Fast, large-scale graph analysis with emphasis on social networks
2. Distributed-memory algorithms with PGAS on clusters
3. Performance analysis, with emphasis on systematic mechanisms for signature capture, bottleneck detection, and refactoring support for HPC applications

Overview: I lead a multidisciplinary group that examines a range of human-centered computing issues. A main area of current research is in “crisis informatics.” This line of research combines human-centered computing and socio-technical empirical study with software engineering; natural language processing and information extraction; information visualization; and network security, privacy and scalability. My group conducts empirical research of on-the-ground emergency activities as well as CMC-based interaction, which has had national and international impact. We continue to drive our results toward design and implementation of new forms of Computer-Mediated Communication for use in crisis situations by both citizens and responders. Our goal is to break new ground on delivering technology innovation to those who are most in need of it.
Background: In an increasingly global society and on a planet experiencing effects of climatic change, large-scale emergencies both instigated by humans and arising from nature can devastate human life and a tightly-woven social fabric. A prevailing hope is that information and communication technology (ICT) aimed at official responders can help reduce impacts of large-scale disruptions, including political crises, natural disasters, pandemics, and terrorist threats. Our program builds on the hopes of ICT, but takes a different approach, focusing instead on an understudied but critical aspect of large-scale emergency response—the needs and roles of members of the public. By viewing the citizenry as a powerful, self-organizing, and collectively intelligent force, ICT can play a transformational role in crisis. Our research aims to leverage the knowledge of members of the public through reuse of publicly available computer mediated communications. The research that our multid isciplinary group will conduct includes the study and integration of heterogeneous information and–with techniques of information extraction through natural language processing as well as trust and reputation modeling–add meta- information to help users assess context, validity, source, credibility, and timeliness to make the best decisions for their highly localized, changing conditions.

Intellectual contributions include the expansion of broad thinking about societal-scale interaction in the area of crisis informatics, and bridging information, cognitive and computer science. This work also includes consideration of implications to emergency management and telecom policy. Innovation will be based on empirical study of CMC and citizen information needs in a range of international crisis events, with the development of methods to analyze such behavior in light of privacy, security, ethical and policy issues. Our project integrates technology and emergency management partners in its mission.
Skills. A CI Fellow working with me is first and foremost encouraged to establish a line of independent research that follows their PhD research trajectory. However, I invite applicants to extend their current research to bridge with our large research venture that includes 7 faculty and numerous graduate students for mutual benefit.

To that end, a number of skills would fit well into our larger research effort: ethnographic research on sociotechnical systems; policy and institutional considerations; systems building of collaborative environments; social network analysis; information visualization; data mining and natural language processing. Previous knowledge and experience with emergency and disaster response is welcomed but not required.

Sue Kase recently did a PhD using a parallel GA on the TeraGrid to optimise the fit of a cognitive model. The data was for stressed and non-stressed and caffeinated and non-caffeinated subjects. The changes in the parameters told us how cognition changed between these groups (sometimes called docking), and her work shows that this approach can be productive but computationally expensive (http://acs.ist.psu.edu/papers/ritterKKBS09.pdf). This is an open area, with more data, more models, and more algorithms possible. We are also creating 1000-node cognitive model networks, and it should be an exciting lab for those interested in these areas of computation, intelligence, and cognition.

The Lydia news/blog analysis project seeks to build a relational model of people, places, and things through natural language processing of news sources and the statistical analysis of entity frequencies and co-locations. Our analysis is quite different from Google News. We track the temporal and spatial distribution of the entities in the news: who is being talked about, by whom, when, and where? Please visit our website (http://www.textmap.org) to see our analysis of news obtained from over 500 daily online news sources.

Now is a particularly exciting time to join the Lydia project ! We have begun active collaborations with political scientists, sociologists, and finance professionals to apply our news analysis to their fields. This opens up Computer Science research opportunities in data mining, machine learning, network analysis, and visualization, We easily keep up with all world’s news feeds plus one terabyte corpus of historical news, thanks to our 28-node cluster and Hadoop-based distributed processing. Our current focus is on NLP, particularly improving our entity recognition and sentiment analysis, in English and other languages.

I also have an exciting bioinformatics project in synthetic biology. Working with virologists, we design virus genome sequences to serve as vaccines, then synthesize our designs to see how they grow! Our work has been in Science and Nature Biotechnology, and is now being applied to several human and animal pathogens.

Attacks and counter measures in newly emerging cognitive radio networks;
Protocols for cognitive radio networking and performance analysis;
Psycholinguistic data mining from text data for deception detection;
Video steganography and steganalysis

Electrical-engineering (ee) degrees. Learning in fields such as art/architecture.
Widely published in archival journals. Three edited books. Authored encyclopedia articles.
Doctorate: dissertation in stochastic control (ee); mathematics and statistics minors; reading knowledge of Russian and French. Now use Google-translate to write Russian.
Rand Corporation employment and UCLA projects on applied problems ranging from operations research to biomedical computing.

Emeritus Professor since 1994.

My research is in Human Centered Computing. The goal of my research is to design, implement and evaluate innovative solutions to real world problems. My research integrates people, culture and technology to address societal issues. In general, Human Centered Computing research is highly interdisciplinary and applied. My areas of specialization within HCC are Natural Interactive Systems, Advanced Learning Technologies/Intelligent Tutoring Systems, Ethnocomputing/Culturally Aware Computing, Human-Computer Interaction, Databases and Data Mining.

In Natural Interactive Systems (NIS), I am interested in creating user interfaces where the user interacts with the system using speech or multimodality. I am researching design, implementation and the evaluation of naturally interactive systems. One of my research projects in NIS is called Prime III. Prime III is a secure, multimodal electronic voting system. Prime III provides an easy to use multimodal user interface that allows greater participation in the electoral process. Voters that can’t read, hear, have visual impairments or physical impairments, can still vote using Prime III.

In Advanced Learning Technologies/Intelligent Tutoring Systems, my research aims to create and study applications that employ intelligent strategies that personalize instruction. In some implementations, this involves the use of spoken language systems and Animated Pedagogical Agents (APAs). I am researching the use and impact of culturally relevant environments that use culture in the education or training environment. This is a form of Ethnocomputing or culturally releveant computing. In my latest research efforts, I am researching game-like interfaces that provide naturally interactive instruction using animation, artificial intelligence, and speech. An example of this work can be seen at http://www.aadmlss.com.

In Ethnocomputing or Culturally Aware Computing, I am investigating the use and impact of culture in computing. Our research suggests that culture can be used to increase interest, user satisfaction and ease of use in computing applications. I am also working on information technology workforce issues. Specifically, I am investigating pedagogies and programs that broaden participation in computing for people in underrepresented groups. I am studying effective practices that help recruit, retain and graduate people from underrepresented groups in Science, Technology, Engineering and Mathematics (STEM).

In Databases and Data Mining, I am investigating data mining for human centered applications, e.g. applications where the data represents people, and tools that answer complex questions from business intelligence, education, and society in general. For example, I use clustering algorithms to process admissions applications in order to increase holistic diversity. This tool is called Applications Quest, http://www.ApplicationsQuest.com. I am also interested in educational data mining.

My research interests lie in human-computer interaction in scientific collaborations, collaborative creativity, cyberinfrastructure, eScience, information visualization, usability in daily life, and how social media and computer-mediated communication are changing scientific practice.

1. Distributed and local research collaborations, and what makes them successful (archival, survey, and qualitative research).
2. Communication and services using human-robot interaction (see Snackbot.org).
3. Visualizations for collaborative analysis.
4. Social Computing.

We are working actively in medical informatics on Electronic Health Records and data analysis of temporal event sequences such as found in patient histories. Our other major effort is on network visualization, related to the NodeXL (www.codeplex.com/nodexl) and other tools, especially as applied to Technology-Mediated Social Participation.

My research interests lie in interactive machine learning, adjustable autonomy, crowdsourcing and human-robot interaction. My work focuses on the development of algorithms that enable robots to operate in unstructured environments alongside humans. This includes policy learning from human demonstration, adjustable autonomy, social robots, and mixed initiative systems.

Online Communities:
How can one structure early experiences in online communities to lead new members to become committed and contribute?

Social impact of computing:
What kinds of social media use by what kind of people influence their psychological well-being and their social relationships.

Virtual organizations:
Groups are inherently different from individuals performing the same task because of a need to coordinate. How can one organize work online to improve coordination?

Health support groups:
How do people generate social support in online support groups and what is its impact?

Large-scale business analytics and Seismic Imaging

1. Large-scale graph analysis on current and emerging HPC systems with emphasis on social network analysis.
2. Performance analysis and tuning for HPC applications with focus on systematic method, knowledge mining, refactoring on massively parallel systems such as blue-gene
3. Fast algorithm implementation and performance debugging with PGAS languages

Our multidisciplinary team at Cornell is interested in using mobile devices to influence healthy behaviors. The goal of our research is to refine and evaluate behavioral interventions to reduce obesity. We are looking at the effect of positive affect, social networks (co-PI on NSF HCC Kleinberg, PI), social support systems, and cell phone apps on creating sustainable eating and physical activity.
We are using mobile devices and feedback tools to collect data on mood and activities and designing visualization tools for participants to reflect on their own patterns and behaviors over time. These tools could be applied to help monitor, change behavior or create awareness in multiple contexts.

http://idl.cornell.edu/index.php

I believe that Post-docs are a time for a newly graduated Ph.D. student to explore and take more independence in their research. I’d like to support a post-doc to accomplish this through the CI Fellows program. That is my primary objective, to help develop a career.

My research interests are in the application of empirical methods to problems in HCI and beyond. I enjoy working on problems that others select where I can provide help and guidance. You can learn more about the types of problems I have worked on at my website (http://www.cc.gatech.edu/~beki). So, if you are interested in empirical methods, particularly qualitative methods, and you have an idea for a project that you think I could help you with, or is related to something I am or have done, send me email!

I’m currently investigating two related areas of work. The first is integrating social networking information plus smartphone data (communication logs + sensor data) to understand human behavior at a fine-grained level and at a large scale. In our past work, we’ve shown how collocations can be used to infer friendships, and how mobility patterns can be used to predict privacy preferences. We want to examine how social graphs plus smartphone data can be used to rigorously understand human phenomena such as leadership, depression, friendship, and what people do in a city, all with an eye towards using this information to create compelling new services for people.

The second area is privacy. One research thrust is managing the privacy of all of this gathered information. Another research thrust is using this smartphone and social graph information to help people manage their privacy and security. For example, how can we use this kind of information to help people manage the 100+ passwords they have, or help configure their privacy and security preferences?

ANDREA: I am a scholar of Public Informatics. This is a term I have coined to best situate my work at the intersection of people, information and technology in a public setting. My work in Public Informatics has contributed to the understanding of the patterns, behaviors and barriers to coordination through technologies among public institutions and contributed to addressing some of the most critical social problems facing the world today, such as humanitarian relief, emergency response, and social and economic development.

DISTAER RESPONSE COLLABOATION: In 2007 I received a grant from the US National Science Foundation to study collaboration and decision-making through technologies among humanitarian relief organizations. This initial seed has spurred my research team to eventually gain three additional grants, and to published five articles and fourteen conference papers from this research. My early findings of this research point to unique network structures and barriers that exist in this form of technical coordination in this sector at various levels of participating organizations. It is in these collaboration efforts that I find global collaboration processes, projects and challenges that are both unique in their context and setting and similar to other IT collaboration efforts more universally. Within this context, information systems collaboration is itself a goal, but it also frequently serves a supporting role in fostering collaboration in other units by promoting enhanced information sharing.
The question that I seek to answer in all of these cases is in what form would technologies have to take to enable fruitful collaboration and information sharing among organizations to improve the delivery of emergency services and goods immediately post disaster.

MICROBLOGGING DISASTER RELIEF: Much has been written concerning the value of using messaging and microblogging data from crowds of non-professional participants during disasters. Often referred to as microblogging, the practice of average citizens reporting on activities “on-the-ground” during a disaster is seen as increasingly valuable. Data produced through microblogging is seen as ubiquitous, rapid and accessible and it is believed to empower average citizens to become more situationally aware during disasters and coordinate to help themselves. However, despite the evidence of strong value to those experiencing the disaster and those seeking information concerning the disaster, there has been very little uptake of message data by large-scale, international humanitarian relief organizations. The real-time message data being contributed by bystanders and those affected by a disaster has been deemed as unverifiable and untrustworthy, and it has not been incorporated into established mechanisms for organizational decision-making. Due to the perceived lack of authentication, large-scale responders have been reluctant to incorporate microblogged data into the process of assessing a disaster situation and the subsequent decision-making process to send aid workers and supplies to disaster locations. Committing to the mobilization of valuable and time sensitive relief supplies and personnel, based on what may turn out be illegitimate claims, has been perceived to be too great a risk. We propose three socio-technical solutions to surpassing adoption bottlenecks, namely bounded microblogging, data as contextual data, and/or use of computational solutions.

Social and psychological aspects of human-computer interaction and computer-mediated communication in a variety of media interfaces, ranging from websites and social media to mobile devices and robots. Current focus is on studying cognitive processing of online information as a function of four classes of technological affordances (Modality, Agency, Interactivity, and Navigability), as predicted by MAIN Model, Interactivity Effects Model, and the Agency Model of Customization. Laboratory-based research emphasizing theoretical contribution to our understanding of how interfaces affect user psychology, with implications for design of future interfaces.

I study motivations and incentives in social media. Specifically, I look at why people contribute to social media systems, and how the underlying technology can influences those motivations and the resulting behavior. I have a major NSF-funded project studying crowdfunding websites (like Kickstarter.com), trying to understand why people contribute, and how we can better design such websites so that people participate. I’m also involved in studying why people make computer security related decisions, looking in particular at their mental models of what threats exist.

In the past, I have been interested in many aspects of computer systems, especially operating systems, networking, and mobile and distributed systems. Current directions I’m looking to push forward include understanding what the mega datacenter and cloud model mean for the future of operating systems, exploring the challenges faced by increasingly high-speed local and wide area wireless technologies, and understanding how to improve the performance and robustness of distributed systems by leveraging the power of social networks.

My research lies in the intersection of AI (ML, agents, text mining, Semantic Web) and Systems (Mobile/Pervasive computing, Web, distributed systems). As recent examples, our group has developed Policy controlled BGP routers that use agent negotiation for automatic fault detection and recovery, Context aware mobile systems for surgery, Social media analytics that factor in both network features and link semantics, Systems that base information sharing decisions on context and policies, System to determine context in mobile systems that respects privacy constraints, and MANETs/CyberPhysical systems whose security/intrusion detection posture is modulated by context.

My research focuses on enhancing the security and performance of computer systems in practical situations. My work targets problems that impact millions of users or mitigates issues with emerging technologies. I build systems and, whenever appropriate, use extensive live deployments to validate their practicality in real settings. Conference and journal publications are an important aspect of impact. But in many cases much more can be done. I believe one should validate and demonstrate the applicability of the research to real world problems. This means that much of my work spans multiple fields, primarily systems and security.

I am interested in mentoring a bright and hard working post doc. My work tends to be quite broad, so the area of work can vary according to the post doc’s interests.

My research focuses on three inter-related streams: the creation of home-based technologies for wellness and health across the lifespan, innovative design methods for ensuring technology development is sensitive to human values, and evaluation of user needs and acceptance of emerging technologies, particularly in residential settings. I also have ongoing research interests in HCI research methods and public policy as it relates to information technology.

Especially seeking postdocs interested in HCI applied to the domains of child & family health, technology use in domestic settings, and video game design.

1. Usability and information visualization applied to biomedical informatics, including bioinformatics and clinical informatics
2. Collaborative data portals in support of bioinformatics, including semantic applications.
3. Translational research tools, including social networking & collaboration finding, coordination tools and resource ontology systems.

My work centers on two areas:
1. Often domestic interactions involve technology and center around gender norms, which makes homes highly gendered spaces. Gender is critical not just in our interpersonal relationships but in how we interact with our environment. The objects and technologies in our homes themselves are gendered, and we respond to social norms regarding gender in our interactions with them. We have additional gender norms surrounding programming of technology devices in the work place, which in turn affect programming of these gendered technologies in the home. As we increasingly introduce programmable technologies into the home, gendered attitudes become enmeshed in how we discuss and use these technologies.

I use ethnographic approaches to create grounded theory that examine gender and domestic end-user programming for computer security, amongst other things. My work discusses how the relationship between technology and identity is negotiated, especially gendered identity and the presentation of an individual’s technical ability. Further, I explore what this negotiation process means for design and evaluation of new technologies.

2. I enjoy working with teams to engage in participatory design in the ubicomp and tangible computing space trying to take the next step beyond fieldwork to create prototypes and engage in iterative interface design. I believe there is work to be done to discuss how the UCD process for ubicomp differs from GUI design, and this needs to be documented and discussed further in the academic literature. This innovative work has led me to recognize the limited applicability of existing usability evaluation methods (UEM), which were largely developed for GUIs. Thus I have developed a strong interest in adapting existing techniques and establishing new methods for evaluating these emerging technologies.

Our research thesis is to develop large-scale data-intensive analytics platform that combines massively parallel data management with massively parallel data analytics, to extract insights from a combination of structured, unstructured, static and streaming data. We also research on novel applications in industrial contexts, such as retail intelligence, consumer social media, environmental sensing and energy production and operations management, that depend on such an analytics platform for scalabiility and performance.
We are particularly interested in candidates who have experience and knowledge in one or more of the following areas:
• Data mining for time series analysis, real time analytics, incremental algorithms, and event stream processing.
• Analytics over mobile social media and information extraction from text; Web 2.0 applications and consumer analytics.
• Implications of multi-core, parallel co-processors, and flash devices on dat a management and analytics
• Large scale data warehousing (data integration, query optimization, workload management), design of robust query processing algorithms and adaptive indexing

* Streaming algorithms and data mining
* Internet Ad Exchanges: Mechanisms, Dynamics, Optimizations, Data analysis. Economics and Game Theory.
* Online Approximation for Internet ad systems.
* Databases: Probabilistic and Stochastic databases.

My research focuses at the CyLab Usable Privacy and Security Laboratory focusses on usable privacy and security. My current projects fall into several overlapping areas: privacy decision making (including applications of P3P), user-controllable security and privacy (including location-sharing privacy and file access control in the home), and usable cyber trust indicators. See the CUPS website for more information.

This is joint work with Lada Adamic (Computer Science, School of Information, Complex Systems). We have an on-going project looking at question-and-answer communities (e.g., Yahoo Answers, Stack Overflow, Baidu, Naver) and social search (e.g., Aardvark, kgb). We are looking for a post-doc who is interested in (1) combining ethnographic and large-scale social network analysis techniques in the analysis of these systems, and/or (2) developing mechanisms and components for augmenting the expertise-finding and question-routing in these systems. For the analysis, we are especially interested in cross-cultural issues.

I am interested in extraction of information from scientific documents to help improve recommendation systems, search engines, etc. We have ongoing projects in table, figure, and algorithm metadata extraction from the CiteSeerX digital library. We are also working on a citation recommendation system for CiteSeerX. As part of a second project, ChemXSeer, which aims to build cyberinfrastructure for chemistry, I am investigating indexes for graph databases. I am also interested in text mining and exploring techniques to extract entities and their relationships in vertical search engines.

Deborah McGuinness is the Tetherless World Constellation (tw.rpi.edu) Chair and professor of computer science and cognitive science at Rensselaer Polytechnic Institute. She has also just been named the director of the new Web Science Research Center at RPI, Prior to joining RPI in 2007, she led the knowledge systems laboratory (ksl.stanford.edu) at Stanford University and prior to that, was part of the AI Research Department at Bell Labs / AT&T Labs.
She co-directs the Tetherless World along with Jim Hendler and Peter Fox.

Her current interests center around making the next generation web more usable and useful. Projects focus on designing semantic tools and applications that help access, integrate, understand, and use data. Current projects include emphasis on semantic technologies, knowledge provenance, privacy, policy, and workflow transparency, semantic eScience, linked open data, trust, social networking, and collaboration technologies, ontology evolution environments, and ethical, policy, and social aspects of web use and usability.

I work in the general area of computer networks, distributed systems, and wireless/mobile computing. My research group explores novel network architectures, protocols, and algorithms that ensure reliable, secure, and efficient operation of large-scale computer networks and enable new, flexible network services. Our approach is often driven by real network and traffic measurements and analysis.

My current interests include:
1. Programmable measurement primitives and architecture that can support real-time traffic analysis and classifications for wide range of applications (e.g, billing, security, traffic engineering, etc.)

2. Measurement-based characterization of online social networks (OSNs) & applications and their implications on network design

3. Provisioning for cloud services

Please refer to RUBINET (Robust & Ubiquitous Networking) Lab website for more details.

My primary research interests are in
data mining/machine learning, high performance computing and database systems.
In our lab we seek to develop efficient and novel
algorithms for managing and analyzing complex data. Our recent research
is particularly motivated by
applications that arise in the area of
network science (specifically biological networks and social networks).
Below we briefly describe two projects in these areas, for others
please refer to the personal and laboratory web pages listed.

1. Architecture Conscious Algorithms and Systems:
Here we have been looking at ways
in which various algorithms (XML indexing, Network motif mining, Frequent
pattern mining) can be re-designed to fully exploit the capabilities
of current day architectures ranging from GPUs to
multicores to supercomputing systems. Of particular interest
is the development of an effective infrastructure enabling such algorithms to
scale to very large data stores .

2. Algorithms and Systems for Network Science:
Here we seek to unravel common principles, events, algorithms and tools that
govern network behavior across different domains ranging from social
networks to biological networks. Of particular interest here are not just
algorithms for module discovery, link discovery,
anomaly detection and event detection
but also usable systems infrastructure that can enable
researchers to effectively
query, visualize,
and analyze such networks under various trust, probabilistic and
provenance models.

If you are interested to learn more about our activities in these areas please feel free to contact me as noted herein.

UC Berkeley’s Laboratory for Automation Science and Engineering, directed by Professor Ken Goldberg of IEOR and EECS, is a center for research in robotics and automation, with current projects in networked telerobotics, computer assisted surgery, automated manufacturing, and new media artforms.

(a) Bioinformatics and Computational Molecular Biology: Data-driven discovery of macromolecular sequence-structure-function-interaction-expression relationships, identification of sequence and structural correlates of protein-protein, protein-RNA, and protein-DNA interactions, protein sub-cellular localization, automated protein structure and function annotation, prediction of functionally important sites in proteins, modeling and inference of genetic regulatory networks from gene expression (micro-array, proteomics) data, modeling and inference of signal transduction and metabolic pathways, comparative analysis of macromolecular interaction networks.
(b) Data Mining: Design, analysis, implementation, and evaluation of algorithms and software for data-driven knowledge acquisition, data and knowledge visualization, and collaborative scientific discovery from semantically heterogeneous, distributed data and knowledge sources, Applications to data-driven knowledge acquisition tasks in bioinformatics, medical and health informatics, energy informatics, ecological informatics chemo-informatics, security informatics, social informatics, e-government, and e-science.
(c) Knowledge Representation and Inference: Logical, probabilistic, and decision-theoretic knowledge representation and inference; Representing and reasoning about preferences. Secrecy or privacy preserving query answering from knowledge bases; Federated knowledge bases and inference algorithms; Description logics; Neural architectures for knowledge representation and inference, Computational models of perception and action
(d) Machine Learning: Statistical, information theoretic, linguistic and structural approaches to machine learning, Learning and refinement of bayesian networks, causal networks, decision networks, neural networks, support vector machines, kernel classifiers,, multi-relational models, language models (n-grams, grammars, automata), Learning classifiers from attribute value taxonomies and partially specified data; Learning attribute value taxonomies from data; Learning classifiers from sequential and spatial data; Learning relationships from multi-modal data (e.g., text, images), Learning classifiers from distributed data, multi-relational data, and semantically heterogeneous data; Incremental learning, Ensemble methods, multi-agent learning, selected topics in computational learning theory.
(e) Semantic Web: Ontology-based user and query-centric approaches to information integration and acquisition of sufficient statistics for learning from data under different access and resource constraints from heterogeneous, distributed, autonomous, ubiquitous information sources; description logics, federated knowledge bases, modular ontology languages, web service composition.
(f) Other Topics of Interest: Biological Computation – Evolutionary, Cellular and Neural Computation, Complex Adaptive Systems, Sensory systems and behavior evolution, Language evolution, Mimetic evolution; Computational Semiotics – Origins and use of signs, emergence of semantics; Computational organization theory; Computational Neuroscience; Computational models of creativity, Computational models of discovery.

Application of complex adaptive systems to:
- economics
- ecology
- policy
- healthcare
- conflict resolution
- social issues
- education
- game theory

Understanding the minimal set of fundamental properties of complex adaptive systems that define the emergent properties of such systems

Understanding the relationship between energy, information, and entropy in complex systems

Defining and measuring the degree of complexity of complex systems

Understanding verification and validation of complex systems

Designing a general complex adaptive systems tool for developing applications in diverse areas

Developing nature/brain-inspired computational platforms

Understanding creativity

General research area: Cognitive, social and computational perspectives on designing and evaluating software for learning, collaboration, and community.

Current focus: Representational affordances in computer supported collaborative learning. Specifically, designing software interfaces to enable learners to construct, discuss, and manipulate representations of their evolving knowledge, and the study of how the notations used in these interfaces affect discourse between learners and learning outcomes.

Uncovering how intersubjective meaning-making can take place through multiple notational tools in computer workspaces, and the roles of language-based and visual/symbolic representations.

Social affordances for online communities, including support for multiple communities and pathways by which participants can discover synergistic value in the larger community.

Prior Activity and Related Interests: Coaching agents, component technology and interoperability (especially at the semantic level), computer mediated communication, networked architectures for collaborative and intelligent learning systems, usability.

My research team is engaged in projects involving design, meta-design, virtual worlds, virtual teams, and collaborative work. We often work on this research in the context of software engineering and particularly, collaborative software engineering. However, we also work in a number of other contexts, such as the knowledge work carried out in large organizations and communities of practice, or the play and work carried out in online games and virtual worlds. Depending on the research context, we perform field (ethnographic-like) studies, laboratory studies, and usability inspections to gather data about people’s behavior. Often our work involves developing prototype software tools or new user interfaces and evaluating them. Sometimes our work is only about observation and analysis.

Recently, we constructed visual tools to help software developers and managers maintain an awareness of distributed software development activities. We are currently investigating ways these same tools can support trust in global software development teams. We also are carrying out a small scale ethnographic study to better understand design in virtual worlds and extend theories of meta design based on our findings.

I have always been keenly interested in what technology and structure imply about human behavior and have a desire to craft work environments that augment human capabilities. An example was my dissertation work about a software tool that improved the performance of otherwise poorer performers on programming tasks without hindering better performers. Thereafter, I was always interested in projects that informed on how individual differences could be reduced. In addition to augmenting human capabilities, I am interested in user interfaces that improve the human experience for their end users. I sometimes think of this in terms of creating more humane interfaces or interfaces that support our humanity. Increasingly, I am drawn to research in the humanities for insight.

I am greatly influenced by the writings of Carl Jung, Herbert Simon, Douglas Engelbart, Donald Schoen, Donald Norman, Marvin Minsky, Mitch Walker, my own graduate advisor, Gerhard Fischer, and his colleagues at the University of Colorado, Boulder, and a number of researchers in Artificial Intelligence, Cognitive Science, Queer Studies, Activity Theory, Participatory Design, Human-Computer Interaction, Computer-Supported Cooperative Work, and Science and Technology Studies.

1. Exploiting physical layer capabilities to design clean-slate (as well as 802.11 compatible) MAC and Network protocols. Interference cancellation, OFDM, smart antennas, cross layer rate control, and related topics are of interest.

2. Also interested in mobile social computing, where we are translating mobile phones into a platform for people-centric sensing.

Technology is rapidly changing the nature of work as we know it. These changes have made possible a variety of new organizational forms but increased the demands on human attention.



We are interested in understanding and optimizing allocation of attention in networked organizations. Our research includes: qualitative study of attention and coordination in networked knowledge work, experiments on task and social influences on direction of attention, quantitative analysis of log data on communication and task-switching behaviors in information centric work settings, and development of novel tools for self-regulation, productivity support, communication management, and coordination in creative work.

IT economics, strategy, and policy issues, including economics of network architectures (e.g., incentive-centered design, industry structure, competition and innovation policy, clean-slate design); economics of information security (e.g., rational behavior, interdependent security, insurance versus protection, risk management); peer-to-peer (p2p) incentive mechanisms and business models; information and communication technologies and development (ICTD).

Today’s interfaces limit our use of computers in two key ways: 1) they are optimized for short tasks rather than the long term activities we carry out in our everyday lives, 2) they constrain where and how computers can be used by not taking advantage of mobility, context, and natural human communication. Our research in activity-based computing addresses these issues. Our systems-oriented HCI research methodology is guided by an iterative design process that can be broken down into design methods, design tools, infrastructure, evaluation tools, and applications.

We are exploring topics in the above areas by developing applications in three domains: 2nd language learning, green behavior, and health and wellness. We are also interested in the cross cultural issues in designing for these domains.

Our approach is to observe target customers in the field, using both traditional and more novel means (e.g., context-aware ESM), and then use the resulting information as a basis for concept design. Designs are then prototyped and deployed on working devices in an iterative manner. Our current focus is on using activity and location inference technologies running on mobile phones to support new applications that help support customer’s everyday lives. We are also building the tools and design methodologies to support these applications as well as the evaluation methodologies required for deploying and testing these applications in the field over long periods (e.g., 3-6 months).

Postdoctoral researchers can explore topics in these areas in the field with me in Beijing, China for the first year and in Seattle for year two. I am happy to work with postdocs whose expertise might be in a range of different HCI subfields, e.g., technical HCI, field work, or design.

I am interested in the use of digital technologies, especially social technologies, by citizens to participate in civic and government activities including voting, activism, and political discourse. I am also interested in understanding voters’ strategies for searching information about candidates and issues and how various types of digital information influence the process of voter decision making. I combine empirical research methods in the usability lab and field with design research on novel interfaces and search systems.

I work broadly in the area of human-computer interaction with a specific focus on information visualization and visual analytics. In particular, my research helps people and organizations who have large datasets that they seek to analyze and understand. We build interactive visualization systems that allow people to explore the data and examine it under different perspectives.

More recently, my work has focused on visual analytics of datasets that are composed of unstructured, semi-structured, or structured textual documents. Large document collections can be found in areas such as intelligence and law enforcement, academic disciplines, consumer product reviews, investigative reporting, etc. We are inventing visualization techniques and building systems to help people who work in these areas to make sense of large sets of documents.

I would, however, be interested in exploring almost any type of data visualization that helps people with analysis. I bring an HCI perspective to these types of problems and my research typically involves much user and task analysis as well as evaluation.

For more examples of my work and the types of projects I do, please see my research group’s webpage at http://www.gvu.gatech.edu/ii.

Cloud Resource Management and Virtualization; P2P and Peer-Assisted Content Distribution; Economics-Inspired and Game-Theoretic Approaches to Resource Management in Distributed Systems and Networks; Formal Specification and Verification of Cyber-Physical Systems; Compile-Time and Run-Time Support for Embedded Real-Time Systems.

I want to enable everyone to access, use and benefit from technology.

My research is at the intersection of human-computer interaction, artificial intelligence and web engineering. I seek a better understanding of how to more effectively present and combine web information sources and have a particular interest in tools that support more accessible, usable and available access for people with disabilities.

I believe human computation and crowdsourcing is part of the solution, and build tools that explore how people can help one another more effectively access the web and deliver information on-the-go. My group has recently been exploring mobile tools for connecting people disabilities to remote workers in nearly real-time to bridge the gap in areas that automated tools are not yet good enough to do.

Finally, research does not happen in a vacuum and I support releasing technology early not only in order to let people benefit from it immediately but also as a way to understand its broader social context.

My research interests currently span the areas of Information Visualization and HCI. I am largely interested in supporting end-users (e.g. knowledge workers, scientists, or children) in both creating visualizations and analyzing data.

We have most recently developed and evaluated a novel method for visualizing the diversity and depth of a pool of objects. This work may apply not only in areas such as university admissions and team building/management but possibly to other areas of ‘design’ such as drug design, or investment portfolio design.

In forward looking research, I am generally interested in understanding how the everyday user is affected by the large amount of data available to them and how they can and do use this data to solve problems and inform decisions and behavior change in their everyday lives. I am particularly interested in the use of visual interaction methods to facilitate this process.

For example, it is becoming clear that sensor technology is going to play an important role in aging at home. Smart homes are being built to monitor elderly individuals, help them in their everyday tasks (activities of everyday life), and to provide feedback to their community of caregivers (care managers, physicians, and family) so that this community can make informed decisions regarding care and to simply put their minds at ease in the specific case of immediate family. Unfortunately, very little work has investigated the use of this vast amount of data to help elderly individuals take care of themselves. With the Center for Healthy Aging Research at OSU, I am currently investigating techniques to better support self awareness through technology. This work applies not only to aging, but to fitness and consumption behaviors as well.

While these are particular projects of interest to me, I am interested in exploring data visualizations in general with a focus on the everyday end-user. For more information, please visit my web page at http://eecs.oregonstate.edu/~metoyer.

Interpretation of human activities using wireless sensor networks and their applications to elder monitoring, security and sensing.

Cyber-Physical Systems for energy management in next-generation intelligent buildings.

Sensor network architectures for the above mentioned systems.

My recent interests have been broadly interdisciplinary, with a particular interest in ways in which computing technology changes the ways we interact and work. Recent projects have included work with humanists in areas such as textual criticism but ranging to affiliated areas such as nautical archaeology and art history. A current project is examining the use of visual materials by scholars in a wide range of disciplines. In more traditional digital libraries, I am involved in a multi-institutional project that is bringing a computing portal to the National Science Digital Library. These research interests are reflected in my other activities, which include key roles in the international digital libraries research community; most recently program chair of the 2009 ACM/IEEE-CS Joint Conference on Digital Libraries.

The Social Analytics group at Carnegie Mellon’s iLab uses language analysis, text mining, information retrieval, and machine learning to investigate research questions related to how people use social media such as wikis and blogs. For example, how do opinion and knowledge diffuse through an organization? What is the relationship between physical network relationships and network relationships established through citation, replying and posting behaviors in blogs? and What are the alternative ways in which expertise can be characterized (e.g., bag of words) and how does the availability and access to such expertise determine outcomes, be they of organizations or of individuals? Research at the iLab is data-driven, and uses both data acquired from public Internet sites as well as unique datasets provided by corporate partners. This project is led by Jamie Callan and Ramayya Krishnan (http://www.heinz.cmu.edu/faculty-and-research/faculty-profiles/faculty-details/index.aspx?faculty_id=51).

I am interested in working with CIFellows in two areas: human computation and computing education.

1) Human Computation: An enormous potential exists for solving certain classes of computational problems through rich collaboration between humans and computers. Currently, countless open computer science problems remain in artificial intelligence, computer vision, and natural language processing. While we continue to work towards completely automating these tasks, for many real-world problems we need an approach today that offers a high quality, inexpensive, and scalable solution.

I am looking for a post-doc that can help build and study systems, help develop a deeper understanding of human participation and the quality of their contribution. I am working in the area of translation, motivated by the need to translate thousands of books from my International Children’s Digital Library project (www.childrenslibrary.org), but expect to broaden the scope to include other domains. I am also interested in developing mobile forms of human participation to reach people where they are.

2) Computing Education: Introductory (and advanced for that matter) computer science students spend a significant amount of their learning time writing programs for class assignments. In recent years, a trend has been to make these programming assignments graphical and interactive in order to make them engaging and show the potential of computers. This has been a positive factor in the recruitment of women, minorities and those students not as interested in computing for its own sake. I propose to go one step further by supporting competitive and cooperative multi-player games among students with the goal of leveraging student’s strong social interests.

Most existing computing competitions (i.e. Netflix, programming contests, TREC, VAST, etc.) are based on having a single input where each competitor produces a solution, runs it against the input, and uses a metric to determine a ranking of winners. Instead, I am building a generic, scalable, gaming engine that lets student write simple independent programs that can compete with each other. I already have deployed it to our freshman programming course this semester in the form of competitive two-player games, but now I’d like to broaden it to include simulations, social and creative systems to have broader reach – and to formally study it to understand how it affects student work.

My research falls into the areas of human-computer interaction (HCI), human-robot interaction (HRI), and computer-supported collaborative work (CSCW). I focus on designing social behavior for socially interactive systems, particularly humanlike robots and agents. This work combines technology development (including machine learning, computer vision, and natural language processing) with exploratory and experimental studies with people (including field and lab studies in which people interact with robots and agents). I am also interested in applications of robots and agents in education, collaboration, communication, disability, and autism therapy and collaborate with domain experts and researchers in these areas, mainly at the University of Wisconsin-Madison.

My research is in the general area of Human Centered Computing. My research interests include virtual reality, virtual worlds, 3D user interface design, multi-modal interaction, virtual human/human interaction, and HCI. Current projects include creating and testing virtual patients for training nursing students in interview skills (with the School of Nursing), developing procedures and evaluating technology to improve vehicle inspection on the assembly line (with Department of Mechanical Engineering and BMW), an experimental investigation of social inhibition and facilitation in avatar interactions in virtual worlds, and the design and construction of multi-touch display hardware and applications (joint with Juan Gilbert’s research group).

I have supervised 10 Post Doctoral Fellows and Visiting Researchers in addition to a number of Research Scientists. Our current research group includes three Ph.D. students (Lauren, Toni, and Jerome), two undergraduates (Austen and Adam), one Post Doctoral Fellow (Dr. Amy Ulinski), Assistant Professor Sab Babu, and myself. During the summers we are joined by 5-8 more undergraduates supported by a NSF REU Site Grant and the DREU program. Our group philosophy stresses team projects, mutual support and mentoring, interdisciplinary research, and frequent meals together.

In addition to my research and teaching, I am also Director of the School of Computing at Clemson University. The School consists of three Divisions: Computer Science, Visual Computing, and Human Centered Computing. Further information of the School is available at: www.clemson.edu/computing .

To achieve truly life-like telepresence, we must better understand key multimedia acquisition, processing, and display technologies. These include video segmentation and matting for background replacement and for gesture-based human-computer interaction, depth sensing, augmented reality, 3D rendering, and view synthesis. We must also understand how to embed these technologies in real-time systems to create seamless and highly intuitive interaction experiences.

My research focuses on the secure and private management of large-scale data. A main goal of my work is to allow for the accurate analysis of data under strong privacy guarantees. Recent efforts have focused on improved mechanisms for differentially private analysis of tabular data, social networks and graph data, as well as transactional trace data.

I am also interested in techniques for improving the security of database management systems, including database forensics, enforcement of retention policies, and models for the protection of audit logs.

Applicants with knowledge of graph or network models, social network analysis, or an interest in differential privacy are particularly encouraged to apply.

I am in the Information School and Human Centered Design & Engineering at the University of Washington, where I direct the Computing for Healthy Living & Learning (CHiLL) Lab. Our primary focus is in Human-Computer Interaction, Ubiquitous Computing, and Persuasive Technology. We are interested in designing, developing, and evaluating applications of computing technology that aim to promote healthy lifestyles and education. We design and develop mobile, persuasive, and collaborative technologies with the goal of helping with record-keeping, review, and motivation to pursue health and educational goals of individuals, families, and teachers. Current projects are focusing on health for families from diverse populations, therapists for children with autism, and individuals with sleep disorders. We are also researching related topics, such as effective persuasive computing and record-keeping techniques and improving the empathy in technologies for health. More information can be f ound at the CHiLL Lab website: http://depts.washington.edu/chilllab

We are interested in understanding and designing systems capable of supporting group interactions and communication in a variety of contextual environments. Our current research programs span a number of areas including understanding how various forms of visual information influence social interactions, building computational models and systems that account for real-time contextual information to support interaction, and developing applications that make use of large-scale community-based knowledge repositories and rely upon this data to develop a new class of “globally and regionally-aware” applications.

I have three main emphases:
1. Creation of online communities to support groups with a geographical basis. Our first and most successful instance of such a community is Cyclopath.org, a route-finder and geographic wiki for bicyclists. I am very interested in creating geographic wikis for other uses, including parents/families and many environmental applications.
2. Developing and evaluating theory-based mechanisms and guidelines for designing online communities. My collaborators and I have tried out many theories from the social science that address issues such as: what makes people get attached to groups, what motivates people to volunteer, what incentives and appeals elicit more and better contribution to group activities.
3. Creating novel tagging algorithms and interfaces. Developing novel metrics for assessing the quality of folksonomies. Developing theoretical models and interaction techniques that situated tagging with other dynamic interaction phenomena like mixed-initiative dialogue.
I also am devoting efforts to two more self-contained projects:
- Creation of an online community for adolescents to promote behaviors and attitudes that limit the spread of HIV/AIDS. Interesting ethical challenges. Chance to create and test persuasive design ideas.
- Empirical study of what factors influence people’s choice of clothing to wear for the day and how satisfied they are with their choices. Creation of a system to enable people to make better choices.
My colleagues, students, and I apply a mix of methods on our projects, including algorithm development and evaluation, invention of novel interaction techniques, user interface design, qualitative studies, quantitative studies especially field experiments, visualization and interactive data exploration, and statistical methods. We work hard to create systems that attract an active user community (like Cyclopath and MovieLens), since these form a very valuable experimental infrastructure in which we can deploy and evaluate empirically new ideas.

I work to develop tools and insights that enable groups of people to work together across the Internet.

My work focuses on SocioTechnical Capital, productive social relations that are enabled by the ongoing use of information and communication technology. Current projects include health and wellness applications that leverage social features, manipulation-resistant recommenders, creating opinion-balanced news aggregators, and detecting and combating rumors online.

I study interesting things like quantum computation (especially post-quantum cryptography and the possibility of algorithms for Graph Isomorphism), phase transitions in NP-complete problems (e.g. the colorability of random graphs, or the satisfiability of random formulas) and social networks (in particular, automated techniques for identifying important structural features of large networks).

My research focuses on social information and social media, with excursions to mobile and multimedia applications. What can we learn from the activity of people on social media services about the world, about society, and about people? How can we improve these services as information platforms?

Join me if you want to develop an understanding of what make social computing platforms (like Facebook, Twitter, Flickr and others) work, and help build the future of these socio-technical systems.

1. Virtual organizations as socio-technical systems
2. Collaboration via large-scale, megapixel displays (e.g., OptiPortals)
3. Impact of cyberinfrastructure on scientific and engineering output
4. Technology-mediated social participation

I am interested in developing new techniques in the areas of academic search engines, image organization using social networking concepts, music information retrieval and advancing search in workflow management systems.

Dr. McDonald has ongoing projects studying Wikipedia and technology and media use in the home. He has published research on collaborative authoring, recommendation systems, organizational memory, and public use of large screen displays, Technology-Mediated Social Participation (TMSP)” and “Social-Computational Systems. His general research interests span Social Computing, Computer-Supported Cooperative Work (CSCW) and Human-Computer Interaction (HCI).

My research focuses on building embodied computational models of human social behavior, especially the developmental progression of early social skills. My work uses computational modeling and socially interactive robots in three methodological roles to explore questions about social development that are difficult or impossible to assail using methods of other disciplines:
1. We explore the boundaries of human social abilities by studying human-robot interaction. Social robots operate at the boundary of cognitive categories; they are animate but are not alive, are responsive but are not creative or flexible in their responses, and respond to social cues but cannot maintain a deep social dialog. By systematically varying the behavior of the robot, we can chart the range of human social responses. Furthermore, because the behavior of the machine can be precisely controlled, a robot offers a reliable and repeatable stimulus.
2. We model the development of social skills using a robot as an embodied, empirical testbed. Social robots offer a modeling platform that not only can be repeatedly validated and varied but also can include social interactions as part of the modeled environment. By implementing a cognitive theory on a robot, we ensure that the model is grounded in real-world perceptions, accounts for the effects of embodiment, and is appropriately integrated with other perceptual, motor, and cognitive skills.
3. We enhance the diagnosis and therapy of social deficits using socially assistive technology. In our collaborations with the Yale Child Study Center, we have found that robots that sense and respond to social cues provide a quantitative, objective measurement of exactly those social abilities which are deficient in individuals with autism. Furthermore, children with autism show a profound and particular attachment to robots, an effect that we are currently leveraging in therapy sessions.

Also see: http://www.yale.edu/socialrobotics