My research concerns the development of efficient algorithms and software
for matrix algebra problems This work began with the development of
innovative memory-efficient algorithms and, more recently, has moved
toward tools to aid in programming of matrix algebra software. I have
recently been collaborating with experts in compiler technology, focusing
on compilers that create fast numerical software. Our initial focus
has been on making efficient use of the memory hierarchy on a single
processor but we are moving into multicore and GPU implementations.
I am also interested in usability of scientific software. To that end,
I am working with collaborators on a tool to automate the construction
of numerical software. Given a problem specification, the tool will
find and tune appropriate routines for its solution.

I was co-developer of an award-winning, NSF-funded undergraduate
curriculum in high-performance scientific computing and have continued
to work on innovative approaches to education in my field. I have
also conducted research on factors that influence women’s interest in
computer science.

My research interests are in security and algorithmic number theory. In the field of security, my research is currently focused on wireless security (ad hoc networking, wireless standards, roaming and handover), privacy enhancing technologies (in particular fairness in privacy-preserving multi-party computations), biometrics (cryptographic key generation from biometrics based on secret sharing techniques), and security economics. In algorithmic number theory, my research is centered on lattice theory (in particular on developing new algorithms and heuristics for lattice basis reduction) and exploring the effective use of GPUs.

My primary research interest is in lifelong machine learning, including:
- statistical methods for knowledge transfer,
- methods for scaling transfer learning to long sequences of tasks,
- sparse representations for transfer learning,
- self-directed goal-driven learning,
- interactive learning in collaboration with a user, and
- the application of these methods to problems in medicine, search & rescue, and space exploration.
I am also conducting research on community detection in relational networks, and AI education.

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

My research group creates new software and algorithms which enable robots to effectively assist physicians and automatically accomplish healthcare tasks. We focus on developing motion planning algorithms and physically-based simulations with applications to robot-assisted surgery, treatment planning, medical image registration, personal assistance, and physician training. Our research spans the following areas:

(*) Motion Planning for Healthcare Robotics: Our objective is to compute actions that enable a robot to automatically accomplish clinical or assistive tasks. Using sampling-based and geometric approaches, we develop algorithms to automatically maneuver medical devices such as robotic surgical assistants or steerable needles around anatomical obstacles to difficult to reach sites, enabling new surgical and interventional procedures. Our research identifies and exploits parallels between medical problems and traditional robot motion planning problems while explicitly considering the complexity and uncertainty inherent in healthcare applications.

(*) Physically-based Medical Simulation: Human soft tissues are heterogeneous and have nonlinear properties, resulting in complex deformations during clinical procedures. Using finite element methods and mesh maintenance algorithms, we are developing simulations of soft tissues and their interaction with medical devices. These simulations can assist physicians in registering diagnostic and treatment images obtained at different times, and can also be used for interactive physician training and procedure planning.

I’m interested in how users manage their digital information through their multiple devices. My work has studied how people re-find information on the web; how people’s mental workload is affected when they move from one device (desktop) to another (phone); and how people use phones in social settings to satisfy information needs.

The rise of social networks presents an opportunity for the management of personal information. Lately, we have begun exploring how to leverage a user’s social network to improve PIM. Emails in a person’s inbox, for example, are “shared” between the sender and the receiver. What if we could share the PIM practices within our inner personal circle? Could we leverage the power of our social network to be more organized? We currently leverage common email patterns to identify spam… we could leverage common PIM practices (tags, filing, organizing) to help others in our inner circle organize their information?

A second area of research, in education technology, is exploring the future of electronic textbooks, particularly as the intersection with in-class management of education. Imagine if lecture notes, assignments, student note taking, readings, and student-to-student discussions, were all managed from a tablet computer. What would our classroom interactions be like? What tools would teachers need to manage the classrooms? What impact on learning would this system have? Can an app be built that guides students towards “today’s” readings and manage their attention to “tomorrow’s” homework?

Anything to do with information. Have been involved in > 110 research grants, giving hundreds of papers and presentations, initially on information retrieval, including computational linguistics and reasoning under uncertainty. Also worked on multimedia, educational technologies, digital repositories, and extending services related to electronic theses and dissertations (including analyzing references and classifying works and parts, see www.ndltd.org), with machine learning. One of the founders of the digital libraries area, developing formal foundations, prototype systems, user studies especially on interfaces and information visualization, and applications including to archaeology, physics, and education. Leading the Crisis, Tragedy, and Recovery network (www.ctrnet.net), including working with ontologies, focus groups, twitter, focused crawling, filtering.

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.

Digital integrated circuits, computer arithmetic, cryptography accelerators, computer architecture.

Harvey Mudd College is a top-rated undergraduate teaching college. Our focus is on excellence in undergraduate teaching. Research largely complements this focus by providing undergraduates a chance to work on important unsolved problems. A CI Fellow at HMC would be heavily involved in undergraduate education in areas such as digital design and computer architecture, VLSI, microprocessor-based systems, and senior Clinic projects. An opportunity exists for a 2-year visiting position from 2011-2013.

My main area of research is Natural Language Processing (NLP), and its application to human-computer interaction, educational technology, and multimedia systems. My goal is to use NLP to support both education and instruction, and collaboration between human or artificial agents. My group focuses specifically on semantics, and discourse and dialogue processing. All my research has its empirical foundations in both qualitative and quantitative corpus analysis, including data mining techniques. In the last decade I have worked on language interfaces for educational technology, on discourse structure / dialogue act recognition, and on summarization. I am currently exploring a new exciting application area, that of health care, e.g. for assistive robotics, decision support systems for patients, and medical education.

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.

In robotics we are interested in motion planning with emphasis on high-dimensional systems and kinodynamic planning, planning from high-level temporal goals, assembly planning, reasoning with sensing and control uncertainty, flexible object manipulation, physical modeling, probabilistic methods in robotics, the geometry of motion, and the use of new enabling technologies. We also develop educational modules and distribute software for teaching motion planning.

In computational structural biology and bioinformatics we develop tools on high-performance systems to model protein structure and function, understand biomolecular interactions and help analyze, in the long run, the molecular machinery of the cell. We integrate sequence information with three-dimensional structural information to analyze and represent molecular flexibility and motion. Our work in computer-assisted drug design has also led us to investigations in systems biology.

Jim Martin, along with Martha Palmer, directs the Center for Computational Language and EducAtion Research (CLEAR) at UC Boulder. CLEAR is dedicated to advancing fundamental Human Language Technology. Our current projects include improved statistical machine translation through the use of shallow semantics, application of NLP and machine learning techniques to electronic medical records, and automatic analysis of social media during natural and political crises.

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.

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,

It is now widely recognized that current commercial many-core systems are simply not good enough: most programmers can’t handle them. Therefore, alternatives must be developed. Anticipating this problem over a decade ago, the Explicit Multi-Threading (XMT) framework has been under development at the University of Maryland. XMT is a general-purpose many-core computing platform with the vision of a 1000-core chip that is easy to program but does not compromise on performance.

XMT is built to support the PRAM theory of parallel algorithm, which is second in its wealth only to the serial algorithms. Since four decades of parallel computing research provided no real alternative to the PRAM, the XMT project sought to draft specifications for the general-purpose many-core desktop of the future, by first inventing hardware and software support for the abstractions developed by PRAM algorithmics — a task deemed impossible by architecture researchers prior to the accomplishments of the XMT project.

A 2010 status report of XMT appears in U. Vishkin, Using simple abstraction for reinventing computing for parallelism, CACM, January 2011. Order of magnitude speedups, dramatic advantages on teachability from middle school to graduate courses have been demonstrated. And favorable student ranking for achieving speedups relative to standard platforms have been demonstrated.

So far, XMT has spanned applications, parallel algorithms, compilers, HW/SW and education of parallelism. Research opportunities building on this promising foundation include now also CS education, bioinformatics, machine learning and other applications, security, OS, and SW architectures.

There is so much more to the potential of many-core parallel computing than the horizons of commercial hardware offer!

The goal of our research is to understand the impact that children can have on the design of new technologies and to understand the impact of that these technologies can have on children’s learning experiences. Our interdisciplinary lab of computer and information scientists collaborate with a variety of partners (e.g., The U.S. National Park Service, UNICEF, Sesame Workshop, The Mongolian Ministry of Education through the World Bank, Microsoft, Discovery Communications, etc.) to develop new educational technologies that range from digital libraries to mobile storytelling experiences.

Our newest work focuses on developing mobile technologies for the “iChild.” The iChild is international, expects to be interactive, is information-active, and intensively social. The mobile technologies we are creating are not for children to consume information, but to create and share information. We are currently working with Nickelodeon Inc., Carnegie Hall, and the U.S. National Park Service to create new mobile technologies that integrate the physical and virtual experiences to tell stories, explore the physical world, and enhance the traditional web experience. Our mobile app building is oniPhones and Android phones.

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.

Storytelling Tools to Teach Computer Programming
Computing has become a fundamental tool in nearly every career field. Yet there are few opportunities for children to learn basic computer programming. We are building a programming environment called Looking Glass (the successor to Storytelling Alice) which provides a fun context for learning to program (building short animated movies) and support for children to learn from each other’s programs. If a Looking Glass user finds a movie on the internet that contains an animation or effect she would like to learn, she can use special tools within Looking Glass to quickly identify the commands responsible for that effect. Then, Looking Glass can generate a custom tutorial that will guide her through building that effect in her own program. We believe that the combination of a motivating context and the ability to find and effectively use examples in programs created by peers will enable many more children without access to formal computer science courses to learn basic computer programming.

Rapid Development Environments for Stroke Therapy Games
Each year there are approximately 700,000 new or recurrent cases of stroke, a number that is expected to rise as our population continues to age. Approximately 50% of stroke survivors experience hemiparesis, the decreased ability to perform purposeful movement. Stroke survivors’ difficulties with purposeful motion often lead to a loss of independence and an increased need for health and social services. Intensive therapy can help stroke survivors to regain motor control lost through a stroke. But, recovery can often involve daily sessions of hundreds of motion repetitions, a process that can often be tedious for stroke survivors. Computer games present an opportunity to embed therapy motions within a motivating context. However, given the unique attributes of individual patients, it can be difficult to create therapy games that are appropriate for a wide range of patients. We are building programming environment that will enable occupational and physical therapists to quickly design therapy games (~1 hour) to suit the rehabilitation needs of individual patients. The games will run on a home computer and require only off the shelf accessories such as webcams, making them broadly accessible to stroke patients. Providing fun therapeutic activities can help to increase the numbers of patients able to fully recover from a stroke. Additionally, the computer games will enable large scale data collection on the effectiveness of different types of therapy.

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.

Iris biometrics, 3D face recognition, biometric and identical twins, face recognition in video, video analytics in autism therapy, disaster damage assessment from aerial images.

We have several interesting projects in computational science education that could use the efforts of a CIfellow to develop effective learning materials across the sciences and math, and with the use of parallel computing in the process.

I invent and evaluate software development tools, especially those that make it easier to find, fix, and understand bugs and usability problems. To do this, I do extensive studies of the contexts in these tools will be used, including studies of novice programmers, professionals software developers, and everyone else who programs. I use a variety of research methods, including lab studies, field work, artifact analysis, and design work.

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 spans a broad range of AI areas, including planning, learning, and multiagent systems. I am particularly interested in interactive AI techniques, the integration of multiple AI techniques, real-world applications of AI, and incorporating various kinds of background knowledge into AI reasoning methods.

Recent research projects include machine learning techniques to handle missing data, interactive and relational clustering, transfer methods for inductive learning, modeling trust in multi-agent systems, preference modeling and learning for decision-making in planning, modeling and learning set-based preferences, integrating HTN planning and RL techniques to develop skill hierarchies, and organizational learning and team formation in multi-agent systems.

I am also actively involved in research on CS education, including diversity issues, intelligent tutoring systems for introductory programming, and developing new curricula and pedagogical techniques for CS education (both at the K-12 level and at the college/graduate level).

Beth Simon’s research interests center on the documented improvement in student learning of computing. She is a leader in adopting and measuring the impact of peer instruction in computing courses — recently using PI as the foundation of the instructional design of a CS Principles pilot. She has previously worked with a post-doc studying the affective impact of adopting “best-practices” CS1 (contextualized computing and PI), using grounded theory to generate a theory for explicating students self-efficacy assessments when doing programming assignments. Beth is interested in computing education research grounded in real classroom activities and in multi-institutional projects defining what the community requires of students to succeed in computing studies.

Anything that involves transforming images into descriptions (or vice versa)

We conduct cognitive science and artificial intelligence research into computational design and creativity. The goals of this research are to model human creativity in practical tasks such as conceptual design of complex systems and to develop interactive tools for aiding people in creative tasks. Our research posits analogical reasoning, visual reasoning, and meta-reasoning as fundamental processes of creativity. Computer-aided design and computer-supported science learning provide two real-world domains for exploring analogical, visual and meta-reasoning. Current projects explore analogical reasoning in biologically inspired engineering design, visual reasoning on intelligence tests, meta-reasoning in game-playing agents, and learning about ecological and biological systems in science education.

matrix theory and computation, large-scale scientific simulations, image data analysis, image reconstruction, algorithm-architecture co-design, mathematical software

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.

I am interested in a few areas at this time – Agile methods for safety-critical software, software engineering education, open source software, technology for supporting engineering education.

Dr. Mohler’s research interests are focused on the implications if spatial ability and visual thinking on the development and production of computer graphics. He also delves into interactive media use for communication and education.

I am interested in changing what we teach and how we teach. In large (300+) classes to small seminars. From CS1 and CS2 to a course that’s IP^2 = internet protocol X intellectual property for non-majors. I’d like to design courses and modules around problems first, techniques and skills seconds. Help change education at Duke and then across the country with the roll out/pilot of a new AP course being developed by the College Board with sponsorship from NSF. Problems are the heart of all these initiatives, but developing and using problems is a complex though rewarding undertaking

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.

Research in the IntelliMedia Group at North Carolina State University focuses on intelligent tutoring systems and game-based learning environments that artfully leverage interactive digital media to create effective, engaging learning experiences. By fusing human language technologies and adaptive reasoning techniques from artificial intelligence with new media and game technologies, we develop and evaluate high-impact interactive learning systems.

My research areas include (1) the development of information data management systems in support of clinical genotyping and personalized medicine, and (2) computational genomics in clinical and non-clinical organisms. In addition, I have experience in commercializing research findings in see-stage companies.

My latest research project is Computational Modeling and Analysis of Complex Systems, a major collaborative NSF-funded project involving a number of institutions. The main Web site is http://cmacs.cs.cmu.edu/. My interests in the project are modeling cellular signaling pathways and designing student workshops to teach the modeling and analysis techniques that we are developing.

I also work in network interoperability testing, development of network monitoring and analysis tools, and efficient MANET algorithms. Recently, I developed a software tool suite called AGATE for generating a collection of state machines representing aspects of the behavior of a network protocol. Earlier, I received a “Best Paper Award” from FORTE/PSTV for a breakthrough interoperability testing methodology developed in a collaborative effort between the Network Systems Research Group at Bell Labs and Lucent’s Next Generation Networking Labs. This methodology has been used very effectively in Lucent’s Next Generation Networking Labs for testing Voice over Packet systems. From 1988-1998, my best-known work was in the area of feature interactions. The primary contributions were a classification of feature interactions (one of the most cited papers in the field); the use of intelligent agents to negotiate the terms of a communication session; and the development of a met hodology and tools for rapid service creation.

My principal research interests are in the area of software engineering, particularly in software development processes and methodologies, software design, and software measurement. My best known work is the goal-question-metric approach to software measurement, my work on the modular structure of software systems, and my work in software product-line engineering as a co-inventor of the Synthesis process, and its successor the FAST process.

My research addresses all aspects of human-robot interaction. Problems include fusing and displaying currently needed sensor data from a remotely located robot, developing control algorithms that allow robots to act autonomously yet ask for help when needed, discovering methods for new interaction paradigms such as multi-touch displays and haptics, and creating metrics for the emerging HRI domain. The two primary application domains in which we explore these problems are assistive technology and disaster response (HAZMAT and USAR).

I also conduct research in the area of using robots in K-12 STEM education, including the development of Artbotics (http://www.cs.uml.edu), teacher workshops (e.g., http://stream.cs.uml.edu) and methods for evaluating such programs.

Bioinformatics: Ontologies and Protein Structure Prediction
Assistive Technologies: non-visual access to the web and to complex data
Declarative Languages: logic programming and constraint programming
Parallel Processing: parallel execution of search problems
Knowledge Representation: planning, action languages, multi-agent systems

My interests span most of “systems”, broadly construed, with a unifying theme of parallelism and concurrency. With the rise of multicore processors, this theme has become central to nearly every aspect of system design. Building on past work in synchronization and microarchitecture, the group here at Rochester has played a leading role in the development of transactional memory. We’re also working on concurrent programming models and language design (for both mainstream and scripting languages), heterogeneous and multicore architecture, and distributed systems with multicore nodes. As the author of a major programming languages text, I’m also deeply interested in how to integrate concurrency into the undergraduate curriculum.

My research is at the intersection of Educational Data Mining and Human-Computer Interaction. I develop and use methods for mining the data that comes out of the interactions between students and educational software, in order to better understand how students respond to educational software, and how these responses impact their learning. I study these issues within intelligent tutors, science microworlds, and educational games.

In recent years, my colleagues and I have developed automated detectors that make inferences in real-time about students’ motivational and meta-cognitive behavior, using data from students’ actions within educational software (no sensor, video, or audio data). We have in particular studied “gaming the system”, off-task behavior, guessing, and slipping. We use these models to make basic discoveries about human learning and learners, and their cognition, meta-cognition, motivation, and affect. My colleagues and I have also developed detectors of
complex aspects of student learning, such as the development of
meta-cognitive strategies and detecting the moment of learning.

I would be interested in working with CI fellows interested in research in these areas.

Our research team (http://www.sis.pitt.edu/~paws/) is interested in all kinds of personalized (user-adaptive) Web systems including adaptive hypermedia, personalized search, and social Web personalization.

We are also looking for researchers interested in personalized E-Learning and in developing advanced tools to support teaching and learning information science and computer science. Our university and Pittsburgh in general is a host for many top researchers in this area (5 out of top 7 authors! http://academic.research.microsoft.com/CSDirectory/Author_category_23.htm )

I seek a postdoc to help run the Software Design and Collaboration Laboratory. The research group has a strong interest in software design, collaboration and coordination, and education in software engineering. We have a variety of ongoing projects, including Calico [a sketch-based software design tool for use on electronic whiteboards], Lighthouse [an Eclipse plug-in that leverages the notion of emerging design to offer advances coordination capabilities], and DesignMinders [a notecard-based approach to knowledge reuse across software design sessions and projects]. We also have strong connections with industry, fueling the projects we work on and providing us with interesting opportunities for testbeds.

Within the broad interests, there is room for you to pursue your own projects, though I would also expect you to join in leading the group, working on grant proposals, papers, advising, etc.

Areas of expertise are human computer interaction, user interface design, usability evaluation and educational gaming technologies. Some of our user studies focus on novice programmers utilizing visual programming techniques (example applications are SecondLife, educational game, 3Dgames). We want to improve user interface design and interaction of applications to improve their practical usage (applications iPhone, WebPages, virtual communities, etc.) In our educational research, we want to capitalize on the dimensions that games can add to computer science undergraduate and graduate curriculum.

Developing and evaluating educational games
Promoting creativity in computer science education
providing intelligent support for learning
Developing and evaluating data-driven methods for intelligent learning support
Developing and evaluating games for health and exercise promotion
involving undergraduates in research
broadening participation in computing
evaluating BPC initiatives
developing games and software for kids to learn computing

Mark Guzdial’s research centers on facilitating student learning through student design, construction, and analysis of artifacts. Philosophically, he is a constructivist, even a constructionist, but he sees a need for support to enable and facilitate a student’s construction of artifacts and knowledge. Mark works on collaborative Dynabooks. He wants to achieve the Alan Kay’s Dynabook vision of a learning machine for developing computational media (where programming itself is a kind of medium). He adds to that vision a desire for a collaborative environment where media can be easily created, shared, and distributed by groups.

Olin provides a unique opportunity to explore contextualized computing/engineering education with a strong design component. My research interests are broad within AI (most recently semantic web/web 2.0 but also including cognitive robotics, HCI, knowledge representation and reasoning, programming languages). I spent ten years on the faculty at MIT before leaving to help found Olin; I would like to share what I’ve learned in both of these contexts. A CI Fellow working with me would have the opportunity to pursue both a research agenda and explorations into curricular/pedagogic innovations, working in a close-knit and collegial community with regular conversation about learning, contextualization, usability. Current and new projects focus on the role of sketching/drawing, mobile devices/social networks, support for aging and/or cognitively challenged populations, and computational thinking/small footprint curricula; collaborations through Olin’s new Initiative for Innovation in Engineering Education would also be encouraged.

Understanding the structure of interacting black hole spacetimes, computational black hole collisions, prediction of gravitational wave signals, data reduction for gravitational wave detectors, scalable computing and computational scaling infrastructure, information security.

The Artificial Intelligence Laboratory at the Computer Science Department along with the Hi-Rise Research Laboratory at the Civil and Environmental Engineering Department have been conducting research projects in the area of planning and scheduling under uncertainty. Current research projects include iterative plan repair in probabilistic domains; generating plans with parallel actions in temporal, probabilistic domains; and developing simulators for assisting construction managers as well as studying expert decision making. The projects share an emphasis on developing effective planning and decision making strategies in complex domains.

• Studying adoption, uses, development, and implementation of innovative technologies, including search behaviors, digital libraries, lecture video, and specific educational technologies.
• User studies of web environments in which users implicitly learn concepts (implicitly: limited awareness that they are participating in a learning task)
• Understanding recruitment, retention, and advancement issues for under-represented groups in computing education and professional careers.
• Study of social aspects of computer science education (higher education).

Medicine is an information-rich profession. The information explosion demands new ways of educating and assessing medical professionals. Successfully navigating information has profound implications for patient safety.

My research interests focus on the use of advanced computer technologies in the continuum of healthcare education. My current work utilizes various simulation techniques (desktop, virtual reality, and high fidelity simulation)in healthcare education and patient safety.

Our research in the Simulation Center includes: 1) investigating the use of simulation in the development and implementation of clinical trials, 2) defining errors and optimizing human performance in clinical trials, 3) investigating “situation awareness” in the perioperative environment, 4) objectively measuring teamwork and communication in high risk medical environments, 5) exploring the use of simulators in the development and evaluation of new medical devices, 6) developing and assessing virtual interactive environments for team training, 7) comparing and contrasting traditional and new forms of team training, and examining what factors differentiate novice and expert healthcare practioners.

I am most excited by research projects that both tell us something new about how people learn and provide a better way of supporting learners. My research focuses on intelligent tutoring systems (ITSs), broadly defined as automated software “tutors” that guide learners as they learn complex cognitive skills, and that use artificial intelligence to adapt instruction to the needs of individual learners. A practical goal of my research is to help make this technology broadly applicable and widespread.

To ensure the real-world relevance of my research, all my research projects involve evaluation of new ideas for learning technologies in real educational settings, although I am increasingly realizing the value of combining field research with laboratory studies. Roughly 40% of my research deals with Cognitive Tutors, a particular type of ITSs developed, perfected, and made classroom-ready in our research group at Carnegie Mellon University (CMU), and widely disseminated by Carnegie Learning Inc., a company founded by CMU for that purpose.

Much of my research takes place in the domain of high-school and middle-school mathematics, but my colleagues and I have also studied learning in ill-defined domains such as legal argumentation, causal reasoning, and intercultural competence, created new ITSs in these domains, and demonstrated that ITSs can be effective in ill-defined domains.

Three main foci of my research are: supporting meta-cognition in ITS, creating authoring tools to make the development of ITS dramatically easier, and enhancing motivation with educational technology.

My colleagues and I demonstrated empirically that students learn better when the tutor supports meta-cognition in the form of self-explanation; improvements developed in this research project were incorporated into Carnegie Learning’s Cognitive Tutor Geometry™, which is used daily in hundreds of US schools. In a different line of research, my colleagues and I have enhanced understanding of the role of on-demand help in learning with ITSs, showing that an automated tutor agent can lead to lasting improvement in student help seeking.

My colleagues and I created the Cognitive Tutor Authoring Tools (CTAT), and created a new paradigm called “Example-tracing Tutors” such that non-programmers can create tutors 4 times faster than programmers used to create them, using programming-by-demonstration techniques. Tutors built with these tools are used in on-line courses offered at CMU (French, Chinese, and Chemistry), as supplement to a college-level genetics text, and in approximately 26 research studies in real educational settings. Currently, we are using CTAT to build a comprehensive open-access website for middle-school mathematics called Mathtutor (http://webmathtutor.org).

A novel direction in my research (and teaching) is educational games. Games and ITSs have complementary strengths. ITS have a proven track record in improving learning, games are very highly motivating. If these complementary strengths could be combined, the effect on learning would be highly dramatic. I am interested in studying how tight the integration between learning and game play needs to be in order to impact student learning.

Virtual Command and Control Systems for Emergencies, Gray literature recommender systems, Collaborative Scenario Creation Planning, Systems, Structural Modeling systems, Risk Modeling, Design of Collaborative Intelligence Systems, Group Decision Support Design

I am interested in computer science education (engaging pedagogy, curriculum development, promoting multi-disciplinary work), machine learning and data mining (probabilistic/Bayesian techniques, SVMs), and information retrieval (web search and text mining). Particularly interesting is work at the cross-roads of these areas, including applying methods from machine learning and statistical data analysis to issues related to education in computer science (seeking to identify patterns or build predictive models) and developing educational materials to better train students in the use of probabilistic analysis. In the latter vein, I have recently developed a course on “Probability for Computer Scientists” (a rigorous undergraduate introduction to probability theory and machine learning), and opportunities would also exist for a CIFellow to potentially collaborate in teaching and further developing this nascent course.

A sociologist by training and computing sciences scholar whose work focuses on “human centered” information systems, Roxanne is currently Distinguished Professor Emerita, College of Computing Sciences, NJIT. Research interests include Group Support Systems (virtual teams and online communities), Evaluation research methods, Asynchronous Learning Networks, Emergency Response Information Systems, Pervasive Computing, and the applications and impacts of “social computing” (“Web 2.0”) systems.

I am looking at innovative ways to save energy at various levels of systems for both sensor and wireless networks, as well as for data centers and server farms. In particular, MAC protocols, DVS scheduling, Thermal Management, on-off configurations, OS and device interactions are of interest.
Another area of interest is CS education. Our new Science and Technology High School and our Laboratory middle-school are fertile grounds for research in what works and what does not, so that we can attract more and better students to CS.

Improving the computational process: Performance modeling of systems and complexity of algorithms and data structures. Queueing theory and mathematical models in applied probability. Specializing in the matrix-exponential processes, which extend Markovian Models, yet allow for correlations and dependencies while preserving the ease of modeling. Algorithms for combinatorial and bio-inspired problems.

My research interests include Intelligent Tutoring Systems (how to build them & how to determine their effectiveness). I want to know how we can get computers to be as effective as good human tutors. I am also interested in Machine Learning and Data Mining, mostly as it is related to Intelligent Tutoring. I am interested in cognitive modeling, which is where we build computer programs that behave the way human behave.

My research will focus on identifying and developing strategies for reuse, which will facilitate novice programmers to create simulations. This work is realized with end user programming/visual programming techniques, and reduces the cognitive baggage of having to first learn to program to attain this goal.

My research will be in the area of End User Programming, a subset of Human Computer Interaction that is a combination of Human Centric Computing, Visual Programming Environments, and Empirical Studies of Programmers. Empirical Studies of programmers normally studies the programming habits of expert programmers, but my approach is looking at novice programmers. The novice programmers group that I will be studying will be high school math teachers. I am looking to create a framework to support their programming of educational simulations with direct manipulation and other visual programming techniques.

Current research interest include development of a 600 node GRID computing facility for use in storage and visualization of SAR Polar data sets. The data is generated through field expeditions to antarctica and greenland. The project is funded through partnership with the NSF Science and Technology Center for Remote Sensing of Ice Sheets( CReSIS). Development of polar science gateways and educational content is also a part of this project.

The research goals of USC’s Computational Emotion Group and ICT’s Social Simulation Lab are to study and model human behavior. Our work on human behavior modeling includes computational models of human emotion, decision-making, theory of mind reasoning and nonverbal behavior.

The Computational Emotion Group also studies the application of these models to the design of virtual humans, life-like facsimiles of humans that look and act like humans and can interact with humans using spoken dialog much as humans interact with each other. Current efforts of the Emotion Group include validating the EMA model of emotion against human data, machine learning approaches to deriving models of nonverbal behavior, the role of physiological processes in emotion and the animation of expressive behavior within the SmartBody virtual human animation system.

The Social Simulation Lab works on modeling and simulating human social interaction, at a more aggregate level (groups, cities, etc.). Ongoing research includes tractable approaches to modeling of theory of mind reasoning and decision-theoretic, descriptive models of human-like decision-making. We also study automated and data-driven approaches to validate and facilitate authoring of large scale social simulations.

Our research focuses on software systems, broadly defined. Areas of interest range from building operating system mechanisms such as lightweight virtualized containers, multiprocessor deterministic record-replay tools, and process schedulers, to creating distributed system architectures for mobile, cloud and autonomic computing. For more information and recent papers, please visit the Network Computing Laboratory website: http://ncl.cs.columbia.edu.

Design Methods: Work starting in the 1960s makes a compelling case that there are commonalities in method that cross specific design domain boundaries. How does designing “work”, and how can (systematic) processes of design be articulated, elucidated, and evaluated? Rather than viewing design simply as creative expression of individuals, or optimizing an objective function, design methods research proposes ways that designers (individuals, groups, or computer programs) can describe design spaces, generate alternatives within those spaces, and evaluate those alternatives with respect to explicit criteria.

Modular robotics promises new, smart, self-reconfiguring materials made of millions of tiny robots that collaborate to shift shape and take new forms. In addition to engineering challenges of building the robots, the programming language challenges of designing ways for a robot ensemble to carry out a task, modular robotics also poses new challenges in interaction: how will people interact with a world made of computationally enabled materials, and how will designers of things made of programmable matter describe the forms and behavior that these materials are to take. How, for example, would we interact with a building that is made of many little robots?

Computationally enhanced construction kits & craft: The toys we play with as children shape the grown-ups we become. Construction kits like Lego and Tinkertoy were materials of making for past generations; now kits can embed computational behavior.

Sketch recognition & pen-based interfaces: People make freehand drawings and sketches to think, communicate, and record decisions. From the informal sketch map showing directions, to the circuit diagram sketched out on the back of an envelope, to whiteboard diagrams made in a group discussion, people find drawings valuable ways to communicate concisely. Especially in design, where early decisions are first approximations and may be contingent, sketching and diagramming provides an appropriate medium. Work on the Electronic Cocktail Napkin — a platform for sketch recognition—led to a set of experimental prototypes that investigated various aspects of freehand drawing, diagramming, and sketching.

Tangible Embedded Interaction: With the embedded/ubiquitous/invisible/pervasive computing revolution, interacting with computers, the traditional domain of “human computer interaction” now blends with the traditional domains of architecture and design, buildings, places, and things. As the physical world is increasingly imbued with computational, programmable properties, how do we design for effective interaction, and how can citizens (so-called “end users”) be empowered to program the behaviors of their physical environments for themselves?

If you choose to work with me you will have the option of working on: (i) an initiative for recruiting young women into and retaining them in computing majors (sites.google.com/site/therprccinitiative), (ii) studies of gender and ethnicity issues in CS/IT/SwE together with an educational psychologist and an IT/Mgt faculty member, as well as with me; (iii) constructing concept inventories for Introductory Programming, Discrete Math, OOA&D, etc with an eye towards using them to understand how to improve curricula.; (iv) real projects for real clients courses; (v) empirical software engineering research

My research focuses on developing motion planning algorithms and physically-based simulations for medical applications, including treatment planning, medical image registration, and physician training. My research spans the following areas:

(*) Motion Planning for Medical Robotics: The objective of motion planning in medical robotics is to compute actions that will guide a surgical device around anatomical obstacles to reach a clinical target. We are developing new motion planning algorithms using optimization and sampling-based methods. These motion planning algorithms must address key challenges that arise in medical applications, including deformations, uncertainty, and optimality.

(*) Physically-based Medical Simulation: Human soft tissues are heterogeneous and have nonlinear properties, resulting in complex deformations during clinical procedures. Using finite element methods and mesh maintenance algorithms, we are developing simulations of soft tissues and their interaction with medical devices. These simulations can assist physicians in registering diagnostic and treatment images obtained at different times, and can also be used for interactive physician training and procedure planning.

Random number generation: pseudo- & quasi-random number generation especially for new architectures via the SPRNG library (www.sprng.org)

Monte Carlo methods and stochastic modeling applied to neuroscience, computational chemistry, and physics

Computational assurance using random number generation techniques

My research focuses on computational models of language understanding and language learning in multilingual settings. Research topics of interest:

-multilingual grammar induction using rich grammar formalisms which combine syntax and semantics,
- context modeling for language understanding
- ontology learning
- terminology acquisition for consumer health systems
- automatic acquisition of conceptual maps for scientific literacy assessment
- informational and conversational language in wikipedia and blogs

Research in the use of advanced architecture computers for modeling and simulation, especially in the area of numerical solutions of PDEs arising from large-scale scientific computing problems. Current interests include applying simulation and modeling techniques in the area of systems biology, tumor modeling, heart simulations and other biological areas, as well as interactive visualization on parallel computers, parallel reservoir/groundwater simulation, turbulent convective flows, multigrid techniques, multi-resolution wavelets and wave propagation.

Research interests include building systems to effectively train, explain and advise users. Extended multimedia capabilities are integrated with knowledge about the user, domain and dialogue to produce real-time performance support and on-demand advisory and tutoring systems. The tutoring systems use intelligent interfaces, inferrencing mechanisms, cognitive models and easily modifiable and customizable software to improve the computer’s communicative abilities.

My current research focus is on text quality—developing automatic measures for predicting how good a text is, specifically text quality for summarization, educational applications and enhancing information retrieval.

The Electronic Learning Communities (ELC) group is focused on using social computing technology to help people to be creative. We study existing systems, especially collaborative systems where people create creative products. Based on what we learn, we design new tools to help people be creative collaboratively, and learn through that process.

The ELC group also focuses on broadening participation in computing, finding ways to leverage teens’ passion for existing technologies to foster an interest in pursuing computing education.

We also do research on Internet research ethics, and how to conduct this kind of human-subjects research in an ethical fashion.

S. Ramaswamy is currently Professor and Chairperson of the Computer Science Department at the University of Arkansas at Little Rock. His research interests on behavior modeling, analysis and simulation, software stability and scalability – particularly in the design and development of better software systems, and intelligent and flexible control systems. He is currently Professor and Chairperson of the Computer Science Department at University of Arkansas at Little Rock. At UALR, he is currently associated with several active research initiatives, which include: the statewide program manager for WiNS (Wireless Nano-sensors and Systems) center, the principle investigator at UALR for a High Performance Computing initiative, and the research coordinator for collaboration on Engineering Innovative Software Systems for Marine Transportation Logistics with the National Institute of Applied Sciences (INSA) in Rouen, France., where he was a visiting research professor in 2006 and 2007. During the summers of 2003, 2004 and 2007, he was a visiting research professor of Computer Science in the Institute of Software Integrated Systems (ISIS) at Vanderbilt University as part of a NSF ITR project – Foundations of Hybrid and Embedded Software Systems. In 1994-1995, and subsequently during the summer months of 1996 and 1998, he was a post-doctoral research fellow / visiting scientist in the Laboratory for Intelligent Processes and Systems (LIPS) at the University of Texas at Austin where he helped with research efforts on Sensible Agents. Dr. Ramaswamy has published over 100 publications and is a featured reviewer for the ACM Computing Surveys. Dr. Ramaswamy earned his Ph.D. degree in Computer Science from the Center for Advanced Computer Studies (CACS) at the University of Louisiana at Lafayette. He is a member of the Society for Computer Simulation International, Computing Professionals for Social Responsibility, a Senior member of the IEEE and a Senior member of the Association of Computing Machinery (ACM).

Development of flexible media streaming systems and applications. Streams might be audio, video or animations that come from live or stored material sources. Multiple stream applications, such as multiple camera collaboration or mixed reality spaces, are of particular interest both for real-time collaboration or event production and off-line viewing and editing. Applications that mix static media (e.g., text, image, etc.) and dynamic media (e.g., streaming media) are of particular interest.

Heterogeneous Parallel Computing
Massively Parallel Computing
Teaching Paralell Programming / Programming Systems
Rethinking the Graphics Pipeline
Simulation and Physically based Graphics
GPU Computing / GPGPU / CUDA

Despite my utterly lack of an updated web page, our lab conducts research in a number of areas, including computer networking (currently supported by two three NSF awards), the design of software and cognitive radio systems (supported by NSF), peer-to-peer software with a particular emphasis on privacy and anonymity (sponsored by parts of the Cable industry). Recently funded projects include ans NSF FIND networking project, compiler validation for DARPA, NSF education grants through the GK-12 program and various gifts from Intel, Google, Nokia and other companies.

Specific areas of interest for post-docs are in cyber-physical systems, reliable reconfigurable systems, compilers and run time systems for multi-core computing.

My own research areas are first-year and non-major CS pedagogy, programming languages, logic, and theory of computing. However, other dept members would also be involved, with interests such as scripting for the blind, database testing, cryptography, and information security. The department is close-knit, and most of us have an interest in the scholarship of teaching as well as more traditional research areas.

My research encompasses both theory (a foundational model for
probabilistic programming languages) and practice (methods for making
code generators reusable). I like to understand and improve software
systems by developing simple formal models with significant
explanatory power. While I have contributed to a variety of topics in
programming languages and software engineering, my primary interests
lie in functional programming and programming-language infrastructure.

I have two new projects, each of which can provide a leadership role
for a postdoctoral scholar:

1. I lead the C– project, whose goal is to make it possible for one
person to build a good native-code compiler for a new language in
one year. We have focused on building a reusable, optimizing code
generator, which has been successful, but we overlooked the
difficulty of building a run-time system.

To build a modern run-time system, you might want to start with
Perry Cheng’s incremental garbage collector, Tim Harris’s software
transactional memory, Cilk’s work-stealing scheduler, Kent Dybvig’s
first-class continuations, and Objective Caml’s constant-time
exceptions. But not one of these elegant, efficient
implementations works with any other, and each one is in cahoots
with the compiler in different ways. Here is an opportunity to
exploit abstraction, modularity, and reuse in run-time systems, so
that we can build state-of-the-art run-time systems from reusable
components. This ambitious goal will require colleagues who have
excellent skills in programming-language infrastructure but also
have experience, taste, and good design sense.

2. Today, most important data is replicated on multiple computers.
Replicated data includes source code under distributed revision
control; electronic mail, which is read and modified on many
devices; and even personal home directories, which may be
replicated both for work on the road and for backup. In all of
these cases, people can make changes at multiple replicas, and
sometimes the changes *conflict*, which means that the replicas
cannot be made consistent without human intervention (called
“conflict resolution” or “merging”).

I have developed an algebraic model of what operations can happen
at a filesystem replica. By reasoning about commutativity and the
happens-before relation, I developed a safe, efficient technique
for identifying conflicts and merging two conflicting replicas. I
believe these ideas will scale to harder problems and to multiple
replicas.

I seek a postdoc who will be able to marry theory to practice,
developing both underlying algebraic techniques and efficient
prototypes that will allow us to test our ideas on version control,
filesystems, and email. The right postdoc will be able to prove
theorems, devise algorithms, and build on (or compete with) such
tools as Unison, git, mercurial, and darcs.

—————-

Both of these projects are just getting started. Either should
provide a fine opportunity for a postdoc to make a distinctive mark
doing something new.

—————-

My record includes an NSF CAREER award, an Alfred P. Sloan Research
Fellowship, and continuous NSF support since 1998. My most recent
postdoc is about to join the faculty at KAIST, a prestigious
technological institute in her home country (Korea).

I am interested in working on cutting edge undergraduate computing education initiatives at all levels of the curriculum. This mentorship will fully engage the post-doctoral fellow in critical aspects of our undergraduate program, and leverage the fellows research interests to expand our current programs in exciting new ways. The research interests of the fellow should match up with current strengths of the School of Informatics, including Human Computer Interaction, Security, or Data and Search. I am particularly interested in working with an individual that is passionate and creative about ways to broaden participation in computing, either through development and implementation of pre-collegiate (K-12) programs or through development innovative programs that enhance student-learning. As part of the fellowship, the fellow will teach new and existing courses, continue their current interests, and start new projects relative to their research interests – articulated with our curricular programs.

Informal Social Learning of Technology, Ubiquitous Learning, Collaborative Information Retrieval, Open Source Software Usability, online technical help-giving, end user software innovation, software informatics, technological appropriation, rapid evaluation methods

I am interested in working on the following topics:

Scientific Discovery through Games.
We are developing new genre of science-centric serious games, including games that lead to scientific discoveries in biochemistry with implications towards curing diseases, discovering vaccines, and developing novel biofules. See http://fold.it, and a recent WIRED article (http://www.wired.com/medtech/genetics/magazine/17-05/ff_protein)

Learning through Games.
Our goal is to quantitatively remove the early mathematics and science bottleneck with a novel learning tool that can be deployed immediately with minimal resources both in and out of school. We will develop, assess and analyze a multiplayer social game designed for the sole purpose of teaching early math to children in the environment that children naturally gravitate towards: social game worlds. This project is a union of game development team, world-class learning scientist’ team, early-math education experts and industry game design experts with a common goal to design a compelling game framework with learning assessment as the primary objective. Ultimately, we intend to develop an open platform where math teachers worldwide can take active part in suggesting and even designing challenges within the game, eventually expanding the game to cover entire middle school math curriculum.

Synthesis of Natural Control Mechanisms.
We are investigating automatic methods for determining the fundamental control mechanisms that give rise to a wide variety of animal locomotion. We are investigating human locomotion control as well as natural controllers for quadrupeds and birds in flight. Our goal is to develop behavior and motion of virutal humans and animals that is indistinguishable from reality.

Dynamics and Control Reduction.
We are investigating control and model reduction techniques that will enable us to automatically reduce the complexity of dynamic simulators. The same techniques should also allow for custom-designed dynamics approximations tailored for specific dynamic control problems.

*** Parallel Web Browsers for Low-Power Devices:

We envision a transition from laptops to handheld computers and predict that the transition will happen only if we rethink the design of web browsers. Web browsers are an indispensable part of the end-user software stack but they are too inefficient for the low-power handhelds. While the laptop reused the software stack of its desktop ancestor, solid-state device trends suggest that today’s browser designs will not become sufficiently (1) responsive and (2) energy-efficient. Browser improvements must go beyond JavaScript JIT compilation. We rely on parallelism and high-level programming languages to achieve these two goals. Motivated by a future browser-based application, we are developing a parallel browser, work-efficient parallel algorithms, and an actor-based scripting language.

*** Programming Abstractions for Algorithmic Software Synthesis

While program verification has recently reached the programmer, the success of synthesis remains in the hands of formal systems experts. To ease the adoption of software synthesis, we are exploring algorithmic synthesis, which is to deductive synthesis what model checking is to deductive verification: Rather than deducing a program using domain rules, algorithmic synthesis finds a program in a space of candidate implementations.

This project investigates linguistic aspects of algorithmic synthesis. Each synthesizer must be “programmed” with the insight about the domain in general and program specific implementation tricks in particular. In deductive synthesis, the insight is conveyed by a domain theory. In our approach, the programmer communicates his insight by writing a partial program, which syntactically defines the candidate space. The partial program is then completed by the synthesizer. Since the program is partially specified, programmer can control the size of the candidate space to make algorithmic synthesis feasible while leaving tedious program details unspecified.

We are addressing three issues inherent to specifying algorithmic synthesis problems: (1) How to debug partial programs? We use angelic non-determinism for gradual partial program development. (2) What is domain insight and how to communicate it? We are developing programming abstractions for defining the candidate space naturally. (3) How to refine the insight to aid the synthesizer? We are investigating methods for carrying out a dialogue with the programmer, with the goal of refining and formalizing her insight.

My general interest are Open Information Systems, or more specifically, Web technologies, ranging from communications mechanisms such as HTTP and SSL to content management and application server programming. My current focus is on the Extensible Markup Language (XML) and associated technologies. I am interested in XML itself and the core specifications such as XInclude, XML Base, XML Namespaces and the XML Information Set. Even though there are numerous technologies for working with XML structures, there is still no decent modeling language for XML, which is another area I am interested in. On top of this foundation, I am interested in XML schema languages (languages, their design, and design patterns for using and combining them) and XSL Transformations. On the application level, my main interests are XML-based information integration, XML-centric software design, XML and databases, and Web Services.

information theory,
physics of communication and computing,
complex and organized systems,
quantum theory of measurement,
reliable communication and computing,
bioinformatics

The Motivational Environments research group advances Human-Computer Interaction methods, theories, technologies, architectures, and environments that incorporate wearable and ambient sensors, responsive spaces, robots and relational agents to promote creativity, teamwork, learning, and motivation.

Affective Learning Companions, real-time multi-modal characters are beginning to sense and respond to learners’ affective cues. Game As Life is extending avant-garde “real-life games” and blurring motivations in everyday digital-physical-social environments. Astronaut Robot Mission Simulators and Pet-Building activities are promoting project based teams and education through novel Human-Robot Interactions. Creativity research methodologies and support tools are being advanced through empirical investigations in research organizations and everyday life experience and through the development computer supported collaborative environments to host a first-of-its-kind distributed NSF Creative IT Workshop.

This suite of technologies and activities is forming a transdisciplinary framework and context to study and foster motivation, learning, teamwork, and creativity. The group is housed in the School of Computing and Informatics and in the transdisciplinary graduate Arts, Media, and Engineering program.

My primary area of research is the long-term curation of digital collections. I’m particularly interested in the professionalization of this work and the diffusion of existing tools and methods (e.g. digital forensics, web archiving, automated implementation of policies) into professional practice. I’m editing and providing several chapters to a forthcoming book entitled, I, Digital: Personal Collections in the Digital Era. I’ve also initiated an international Personal Digital Archives Working Group (PDAWG).

The VidArch project (http://ils.unc.edu/vidarch/) has investigated the collection of online video, with a particularly emphasis on contextual information. My contributions have included an information model for contextual information in digital collections (http://sils.unc.edu/research/publications/reports/TR_2007_04.pdf) and several empirical studies of online selection and collecting strategies.

Other current projects include DigCCurr and DigCCurrII (http://ils.unc.edu/digccurr/), which are developing and implementing courses of study and practical engagement opportunities in digital curation. I’ve developed an extensive Matrix of Digital Curation Knowledge and Competencies (http://www.ils.unc.edu/digccurr/products.html), based on various data sources and grounded in professional literature.

Past research projects have included CAMiLEON (http://www.ils.unc.edu/callee/dig-pres_users-perspective.pdf), which examined migration vs. emulation as digital preservation strategies; and an in-depth case study of the development of the OAIS (http://www.ils.unc.edu/callee/dissertation_callee.pdf).

My current research interests include Internet application performance and measurement, privacy measurement and protection, utility computing and home network measurement. More generally my research interests are distributed computing, networking, and user interfaces.

Our current department has nine faculty members with a range of specialties. Because ours is a small, undergraduate-only program, the primary undertaking of a CIFellow at Harvey Mudd College would be teaching. Thus, we are seeking passionate teachers first and foremost. There will be opportunities (1) to co-teach introductory courses (2) to develop and deploy one or more advanced electives in an individual area of specialization and (3) work with students on (your own) research projects accessible to talented undergraduates.

Our curriculum also offers an unusual opportunity to co-advise a year-long “clinic” project, in which four undergraduates specify, design, and deliver a finished product to a sponsoring company. Because of this “clinic” program, software engineering is of particular interest to us.

I have a broad interest in software engineering, particularly in software testing in complex environments (eg. a networking environment). I plan to continue this research to help manifest practicality within current testing processes.

I also do research in computer science and software engineering education to attract and retain students in computing fields.

My research interests span the following areas: (1) logic programming languages, with particular focus on integration between paradigms and parallel execution models; (2) development of ontologies and workflow languages for bioinformatics; (3) languages and algorithms for reasoning about actions and change in domains with incomplete knowledge, and with multiple interacting agents; (4) assistive technologies for individuals with visual impairments, with particular focus on web accessibility and accessibility of mathematical content.

MESL research interests span from theory and design methods for building (energy, performance) efficient systems to algorithmic aspects of power management and sensor network simulations.

Our recent contributions include SystemC modeling and SPARK parallelizing high-level synthesis, both of which are publicly available and have been incorporated into industrial practice. Earlier Gupta lead the Adaptive Memory Reconfiguration Management (AMRM) project supported by DARPA/ITO under the Data Intensive Systems (DIS) program which demonstrated methods to optimize movement and placement of application data across the memory hierarchy. He also co-lead DARPA/ITO supported project on Compiler Controlled Power/Performance Management (COPPER) under the Power Aware Computing and Communications (PACC) program.

Our ongoing efforts include energy-efficient data-centers and large scale computing using memory-coherent algorithmic accelerators and non-volatile storage systems.

Because of my own background in design automation, there continues to be work in synthesis, optimization for system level designs. Our more recent work related to high-level verification techniques using refinement checking methods.

High performance computing (HPC), international engagements in HPC, cyberinfrastructure for societal advancement and inclusion, issues related to gender and diversity in computing, cyberinfrastructure education, tools and technologies for impacting education, electronic medical records and health informatics related to child health and obesity monitoring,

end-user programming, scenario-based design, case-based learning, computer-supported cooperative work, social networking systems, computer-mediated communication, community informatics, usability methods, usability engineering, end-user software engineering, gender & CIS, computer science education

Research focused on games and their applications including a games engine for kids, DDR for the elderly, and games in CS classrooms.

software engineering; software quality; software measurements; self-healing software systems; data mining; machine learning; medical informatics; computational intelligence; computer and data security.

Dr. Peter L. Elkin is a Professor of Medicine at the Mount Sinai School of Medicine. He is the Center Director of Biomedical Informatics and the Vice-President of Mount Sinai hospital for Biomedical and Translational Informatics. He received his Batchelor of Science from Union College and his M.D. from New York Medical College. He did his Internal Medicine residency at the Lahey Clinic and his NIH/NLM sponsored fellowship in Medical Informatics at Harvard Medical School and the Massachusetts General Hospital. Dr. Elkin has been working in Biomedical Informatics since 1981 and has been actively researching health data representation since 1987. He is the primary author of the American National Standards Institute’s (ANSI) national standard on Quality Indicators for Controlled Health Vocabularies ASTM E2087, which has also been approved by ISO TC 215 as a Technical Specification (TS17117). He has chaired the OASIS International Healthcare Continuum and served as a co-chair of Health and Human Service’s HITSP Technical Committee on Population Health. Dr. Elkin served as the co-chair of the AHIC Transition Planning Group. Dr. Elkin is a Master of the American College of Physicians and a Fellow of the American College of Medical Informatics. Dr. Elkin chairs the International Medical Informatics Associations Working Group on Human Factors Engineering for Health Informatics. He was awarded the Mayo Department of Medicine’s Laureate Award for 2005. Dr. Elkin is the index recipient of the Homer R. Warner award for outstanding contribution to the field of Medical Informatics.

The focus of my research is on the development and evaluation of tools for visualization and interaction in support of complex tasks. As such, it includes work both in human-computer interaction and in the domain of the complex task to be supported.

Early work addressed visualization and interaction in support of program comprehension and performance evaluation of parallel and distributed systems. Research in techniques for interactive steering built on this early work.

Later work involved the development and evaluation of numerous domain-specific tools employing visualization and interaction, with a strong focus on applications in Bioinformatics.

More recently, I have begun a program of research that attempts to answer questions about what types of displays are useful and usable, and what properties of those displays promote or inhibit understanding and usability. I am currently involved in research on the effectiveness of various types of software engineering displays and tools for concurrent systems. We study this problem in the educational context and seek to extend our findings to practitioners. We are particularly interested in studying the nature of the novice to expert transition and how to facilitate users as they move along this spectrum.

I also work with the EupathDB group on the design, evaluation and development of user interfaces and visualizations for web-based biological databases and tools. Our Web Effectiveness group focuses on user modeling and effectiveness evaluation in this context

My research focuses on the security and availability of complex distributed systems. To date this has included the characterization of specific network threats (e.g., worms) and techniques for measurement of these threats at scale (e.g., distributed network telescopes). More recently I have been focused on the interplay between the attackers and the defenders of these systems including the creation of techniques that allow defenders to hide from attackers as well as through the classification and analysis of complex attacker tool ecosystems.