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.

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.

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.

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.

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.

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.

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.

Improved algorithms for iris biometrics, improved algorithms for face recognition, multi-modal biometrics, data mining

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.

My group has developed middleware, FG (http://www.cs.dartmouth.edu/FG/), which helps to mitigate latency in data-intensive programs. With FG, the programmer structures the computation as one or more pipelines (not constrained to be linear pipelines), where stages work on buffers asynchronously. This work came out of real implementations of out-of-core algorithms for the Parallel Disk Model, but it applies to much more than the PDM. I’m looking for a creative researcher to help us extend what FG can do and to help us incorporate FG into real applications.

Another line of research that I’m just getting started on is computer science writing. What makes good papers? Bad papers? How can we communicate our ideas to other humans more effectively? I recently spent four years directing the Dartmouth Institute for Writing and Rhetoric, so this research direction follows from my experiences there.

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.

My research concerns the development of efficient algorithms and software for matrix algebra problems. Recent work has been done in collaboration with experts in compiler technology and focuses on compilers that create fast numerical software. I am also interested in and have conducted research on both undergraduate education in computer science and factors that influence women’s interest in computer science.

Computational science has transformed the scientific process but has yet to make its necessary impact on education of graduate, undergraduate, and pre-college students. At Shodor we are leading the effort to transform learning through computational thinking. By developing research-quality simulations and computational tools, Shodor is helping develop the next generation computational scientist capable of combining quantitative and qualitative models, analogous thinking across disciplines, and multi-scale modeling. We are at the leading edge of petascale applications, while still working in the classroom setting. I am looking for dynamic individuals capable of collaboration with the best math and science practioners and educators. I am looking for persons who understand the power of dynamic representation and modeling and can build effective learning environments that bring young learners to want to be scientists who use computing in new and exciting ways to model and master the world around them. You should have a solid background in more than one of the following areas: computing, mathematics, science, humanities, education. I am especially hoping to find persons with an interest towards developing effective learning modules in multi-core/many-core systems in support of the Track 1 and Track 2 Petascale Computing Facilities funded by NSF.

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.

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.

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?

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

Our research team (http://www.sis.pitt.edu/~paws/) is interested in all kinds of personalized (user-adaptive) Web systems. It includes socially-adaptive systems providing community-level personalization. We also work on a range of advanced tools to support teaching and learning information science and computer science topics.

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

The Bioinformatics and Intelligent Systems Lab at USM focuses on evolutionary
computation and other artificial intelligence approaches as applied primarily
to bioinformatics and intelligent agents.

Bioinformatics projects include:

GAMI, a genetic algorithms approach to DNA motif inference: In this project we
identify patterns in noncoding DNA that have been conserved across
evolutionary time; such elements are good candidates for affecting the
function of genes and will be studied at the bench by our biological
collaborators. This project is motivated by a study of CFTR, the gene for
cystic fibrosis and has expanded to other environmental-response genes; among
GAMI’s strengths is that it is designed to work with long sequences (e.g.,
100k) and many of them (e.g., 100 or more) There are many subprojects here;
one particularly important horizon is that functional elements in noncoding
DNA tend to appear in modules (not in isolation), and we will design a new
system to infer these.

Gaphyl, a genetic algorithms approach to phylogenetics, the inference of trees
representing the evolutionary relationships among species or strains. We are
just starting a swine flu project, which will also mean designing a new
computational approach designed to work specifically with viruses.

My bioinformatics work is collaborative with researchers at the University of
Maine (Orono), Dartmouth College, the Mount Desert Island Biological Lab,
the University of Illinois.

Our recent intelligent agents work has focused on game-playing agents. We won
first place in the 2008 Ms. PacMan competition at the World Congress on
Computational Intelligence (Hong Kong) and the 2009 Unreal Tournament
competition at the Congress on Evolutionary Computation (Trondheim,
Norway). Designing agents for interactive dynamic games is a very similar
research problem to real-time robotics, where inputs must quickly be processed
to determine appropriate outputs, and split-second decisions must be
made. While the competitions have been won with non-learning systems, our
primary interest (and current efforts) are on learning in these environments.

Other projects include:

Lobster CyberCatch, an educational science game designed to teach
middle-school students about math and science concepts in general and lobsters
(and lobstering) more specifically.

VIEWER, a project centered at the University of Maine (Orono) to develop
touch-screen visualization walls for remote conferencing for scientific
collaborations, including informal “water cooler” conversations.

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 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 is a collaboration we have just begun with the Weill Music Institute at Carnegie Hall (NYC). The focus of this partnership will be to create online tools for social musical interaction that can be accessed with traditional desktop/laptop technologies and with the use of new mobile technologies. We will ask with this research, how can students share musical energy, artistry, and cultural understanding with the bandwidth of online communities, mobile media, live distance ed technologies & digital libraries?

The educational programs at Carnegie Hall take place on a world-wide stage serving students in Istanbul to Mexico City to New York City. There is also a model school in Harlem, NY where new ways of infusing music into all parts of the K-8 program are being explored. The computing tools we will be building bring together social computing with advanced digital libraries to expand the possibilities for music education.

The Department of Computer Science at Trinity University is looking for a CIFellow who has a passion for teaching in an undergraduate institution and doing research with students. Any area in computing is welcome. Our Department has eight tenure-track or tenured faculty and three instructors. We provide excellent liberal arts and science education to a highly selective student body. During the CIFellow’s tenure, we will provide him/her with opportunities such as:
1) Teach a variety of introductory CS courses such as CSCI 1311 (Intro to Programming Logic) and/or CSCI 1320 (Principles of Algorithm Design – I).
2) Create new elective course(s) in the individual’s area of expertise.
3) Do active research with our talented students.
4) Create his/her own interdisciplinary First Year Seminar to enhance the Common Curriculum in the liberal arts and sciences at Trinity.

The CS Department currently has several NSF funded programs that can help the CIFellow to achieve his/her teaching and research goals in an excellent computing environment, such as REU Site (Research Experiences for Undergraduates) and MRI (Major Research Instrumentation). Our faculty collaborate significantly with other departments in research and teaching, such as Biology, Physics, Sociology, Neuroscience, Economics, and Communication. For example, the DIAS lab (Distributed Intelligent Agent Systems) is currently developing a multi-agent system in social environments. This multidisciplinary project involves Computer Science, Sociology, and Neuroscience. Because of this, AI and related areas are of particular interest to us.

Also, though it is not an active area of research in our Department, San Antonio is a major center for Information Assurance & Security (IAS). NSA and the military have major installations here; and it was just announced that the new Air Force Cyber Command Headquarters will be located in San Antonio. So there would be ample opportunities for IAS work locally as well as course development in our curriculum. These are just two examples; graduates in all areas of computing are welcome to apply.

The CS Department anticipates one to three tenure-track openings over the next few years, so it is possible that the postdoc position could become tenure-track at that time.

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.

My current research interests are 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 methodology and tools for rapid service creation.

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).

The Center for Computational Language and EducAtion Research (CLEAR) is dedicated to advancing fundamental Human Language Technology and applying it in critical areas including personalized learning, medical informatics, and crisis informatics.

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

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. The theoretical aspects of my research concern the linguistic analysis, and the knowledge representation and reasoning that support the understanding and generation of NL discourse and dialogue. All my research has its empirical foundations in both qualitative and quantitative corpus analysis, including data mining techniques. In the last decade I have primarily worked in language interfaces for educational technology. 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.

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 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 interative and relational clustering, transfer methods for inductive learning, modeling trust in multi-agent systems, state-space analysis techniques for constructing plan libraries to speed up planning, preference modeling and learning for decision-making in planning, modeling and learning set-based preferences, organizational learning and team formation in multi-agent systems, and multiattribute optimization and visualization for school
redistricting.

I am also interested in research on diversity on CS education, and in developing new curricula and pedagogical techniques for CS education, both at the K-12 level and at the college/graduate level.

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 research and educational career straddles the border between computational theory and mechatronic engineering: rigorous mathematical results enable engineering advancements while the practical aspects of implementation drive theoretical pursuit. Toward this goal, I have created comprehensive programs in snake robots and in coverage tasks as foci for my research to date. Snake robots can exploit their unique shape and many degrees of freedom to thread through tightly packed regions, accessing locations that people and conventional machinery otherwise could not. Working with practitioners in their respective fields, my group has been active in applying these mechanisms toward minimally invasive surgery, urban search and rescue, and manufacturing of aircraft wing assemblies.

The application of robotics for searching minefields has inspired my group’s research in coverage, where a path planner directs the robot to pass over every point in a target region. Bayesian-estimation techniques were then developed so as to only cover a small fraction of the overall area while passing over most of the targets. We also extended this work into higher dimensions to develop motion planning techniques to automate car painting.

For both snake robots and coverage, my research program builds upon fundamentals in robotics, including mechanism design, path planning, motion planning, and estimation. These problems are important because once the robot is built (design), we must decide where it should go (path planning), determine how to get there (motion planning), and close the loop (estimation) to inform the planners and controllers. Much of the novelty in my approach arises from the use of topological structures to reduce complexity, combined with geometric reasoning to guarantee performance. The resulting mixture of discrete and continuous aspects is unified through hybrid system concepts that allow seamless connections between high-level discrete abstractions and low-level control policies and estimation schemes.

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. This philosophy has been the cornerstone of my graduate course, Robotic Motion Planning, which has resulted in a co-authored textbook on motion planning. Also, guided by this philosophy of mathematical and experimental rigor, I designed and continue to teach an undergraduate class, Introduction to Robotics (16-311), that makes use of LEGO robots to reinforce basic principles taught in class. This course provides the basis for the undergraduate minor in the Robotics, which I founded and directed since its inception. This minor is one of the first undergraduate certifications for robotics in the world.

Looking into the future, my group will continue to develop mechanisms for search and rescue, minimally invasive surgery, and archeology. We are, however, interested in building other novel robotic mechanisms: a small surgical snake robot for natural orifice transluminal endoscopic surgery (NOTES), a soft robot for novel locomotion, a spider robot with dynamic soft legs for wall climbing and jumping, and mechanisms to assist the disabled. Naturally, each of these mechanisms emits new theoretical challenges. Specific problems we will be investigating is adapting our locomotion work to articulated swimming and amphibious vehicles, developing new measures of manipulablity and maneuverability, using topology to reduce the computational complexity of both SLAM and multi-robot coordination, and placing all of these in a hybrid control framework.

I am looking for a post-doc candidate who not only shares some of my current research interests, but also those looking forward. I am also seeking a candidate who is interested in either education or entrepreneurship (or both). I would include this candidate in my course experiences and if desired, co-develop new curricula which the candidate can use if he decides to pursue a faculty position. In addition to education, I believe entrepreneurship can also support impact

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.

As an HCI researcher and teacher, I’m fascinated by software. I’m intrigued with how it’s built, the people who build it, and its far reaching effects on society. I study beginners, end-user programmers, and professionals with lab studies, classroom and corporate field work, and artifact analysis. I use the results to invent tools that better support the design, creation and repair of software.

I work on and think about how to communicate ideas and concepts in the classroom and the broader community; how to make classes intellectually compelling, deep, and exciting to undergraduates in a variety of disciplines; and on constructing a portfolio of interdisciplinary problems and stories on which to build examples and courses.

I propose a mentorship to help gain experience and expertise in teaching: from large classes in technology and policy to smaller classes in programming and software design to seminars in any area. I’m proposing a teaching mentorship, but i hope that the post-doc applicant will continue with her or his research, collaborating with other faculty in our department. But this experience is primarily about on-the-ground, in-the-class teaching experience: together and on your own.

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.

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.

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.

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 integrating heterogeneous data and models.I’m particularly interested in the use of semantic technologies to support scalable provenance and the development of advanced capabilities such as digital watersheds that provide web 2.0 visual analysis capabilities over distributed data and computational capabilities. I am looking for individuals interested in research with application in support of scientific research and 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.

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.

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.

My main research goal is to develop innovative techniques, tools, and applications that improve the overall experience between humans and machines. More specifically, I am interested in the creation and evaluation of advanced interfaces that support education, entertainment, and general work productivity.

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, 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.

I have several research projects on provenance in workflows and databases, with applications in biology. Candidates must have a track record of research in databases or workflows, and an interest in interacting with biologists. Candidates with experience in interacting with biologists are of particular interest. The projects of interest are ZOOM*UserViews and Providing Provenance Through Databases and Workflows (see http://db.cis.upenn.edu/research/ for details), which deal with the issue of data provenance. Our research projects aim to efficiently query and store provenance information in databases and workflows, and understand how to integrate provenance across databases and workflows.

I am also interested in educational techniques that draw women and minorities into computer science, and have recently started collaborating with Yasmin Kafai in the School of Education on Service Learning Courses that reach out into the community and involved Penn undergraduates (see http://www.seas.upenn.edu/~awe/ for other activities in this area). Candidates in this area should have experience in CS education and/or outreach.

My work involves the social, historical, and policy aspects of IT as broadly conceived. Recent projects have included the social informatics of diabetes, the Internet and American business, information seeking behavior in everyday American life, the history of privacy in America, offshoring of IT services, interdisciplinary scholarship on digital media, the underrepresentation of women in the IT field (especially as related to entrepreneurship), the history of IT, uses of IT to automate or augment historical and archival practice, and social and economic analysis of the Internet (blogging, social network sites, online dating, political action, strategy and structure of the industry, etc.).

gaze-contingent interaction, eye tracking, virtual science labs for middle schools, studio-based learning in computing, computer-supported collaborative learning, algorithm visualization, cognitive modeling and simulation

I am interested in a few areas at this time – software engineering education, particularly problem and project-based pedagogy; reverse engineering to produce models for validation; and the relationship between agile methods, open source, and quality software for safety-critical domains.

See last 7 papers on my URL. I have been working for the last
15 years on the design of a coherent purely relational (declarative, logic) programming language. There are lots of unsolved, challenging problems to choose from.

I lead the group that develops, supports, and applies the Swift parallel scripting language (http://www.ci.uchicago.edu/swift) to high performance scientific computing problems on clusters, grids, clouds, and petascale supercomputing systems. We apply Swift to large-scale computing problems in neuroscience, molecular dynamics, genomics, proteomics, bioinformatics, energy/climate/economic modeling, and the social sciences.

Information and Communication Technology for Development; Distributed, pervasive, and mobile computing; parallel shared memory computing, including: distributed information management, high performance networks, parallel programming environments, DSM systems, and parallel operating system / architecture interaction; Digital inclusion; CS and Engineering education and outreach; Autonomous robot control.

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.

The Liquid Narrative research group at North Carolina State University’s Computer Science Department works in the area of procedural content generation — the creation of content for interactive games and other virtual environments — that uses models of narrative to build stories and tell them automatically. Our work uses techniques from Artificial Intelligence, Computer Gaming, Human-Computer Interaction, Virtual Reality and Cognitive Psychology to model narrative aspects of human interaction with computer systems. Our investigation is motivated by fundamental ideas from narrative theory and artificial intelligence and looks to provide computational models of interaction useful across a wide range of applications including

* education
* training
* entertainment
* computer-mediated communication
* collaboration and social interaction

Colleagues in the LN lab work closely with other faculty and students in NCSU’s Digital Games Research Center where 15 faculty from across the university collaborate on a number of multi-disciplinary research and teaching efforts.

Michael’s current work focuses on a) intelligent control of a 3D camera within a story-oriented environment, b) extensions of current models of story structure building on plan-based models to account for narrative features like character conflict and the dynamics of a character’s plans and beliefs, c) the interplay between the knowledge of characters, the knowledge of a game player and the knowledge of a storyteller to create a range of narrative structures and d) the application of these and other AI techniques to create computer games for learning, entertainment, training and other novel contexts.

My research area is methods and theory in human-computer interaction, especially scenario-based methods for design and development, minimalist techniques for making information engaging and efficient, computer support for collaborative problem-solving and learning, community informatics – especially mobile community networks, social impacts of computing, and social sources of creativity.

My current projects and interests all focus on collaboration. I am interested in how people solve problems, how they learn and make sense with others. I am interested in critical social-cognitive concomitants of such as trust and social capital, sense of community, and collective efficacy. And I am interested in developing better methods and techniques, and better computational tool support for collaboration. Our group has always pursued a very broad approach to social and cognitive analysis, that is, through laboratory analysis and fieldwork, through session logging, performance criteria, surveys, interviews, and ethnography. And we have always integrated and cross-leveraged social and cognitive analysis with software creation and prototyping. Much of our work involves working in real domains, and when we do this, we typically work with users as collaborators. This style of participatory action research (PAR) is not only afforded by human-computer interaction. HCI demands it. It makes HCI in general, and in our group especially, very exciting.

My current work focuses on developing a better understanding of what collaborative knowledge work is (which seems like it should be a solved problem, but is not), and on developing new kinds of visualizations and other tools to support complex collaborative work. For example, I am investigating and developing tools to diagnose and to teach collaborative self-regulation skills, so as to allow teams to actually collaborate, and not merely divide up their work to minimize overheads of coordination. I am also investigating and creating tools to support activity awareness in collaborative interaction: how teammates build common group into shared practice to generate and enhance identity and social capital. After all, to collaborate effectively one needs to be aware of a lot more than where one’s partner is pointing a cursor. One needs to know what partners know that might be relevant, what partners value, what they like to do, what they do well, what they want to do now or soon, and what criteria they might use to evaluate joint outcomes. All of this evolves continually.

I tend to address my own design research to relatively complex activity domains, such as information analysis, emergency management planning, community informatics, teaching/learning usability engineering, and software design. I am investigating the conjecture that complex activity provides resources that that facilitate the creation of tools that support human performance at levels beyond what is possible when working face-to-face, without computer mediation.

Spoken dialogue is a natural and highly desirable form of student-computer interaction, which provides both opportunities and challenges to both dialogue-based tutoring systems, and to spoken language systems. The goal of most of my research is to wed speech and language technology with instructional technology, in order to promote learning gains by enhancing communication richness.

I work on genome analysis and am particularly interested in how to apply existing tools and technology to existing problems; this means less algorithm development, more large-scale data analysis, software engineering, and HCI.

algorithmic and applied aspects of genome rearrangements, DNA fragment assembly and computational proteomics.

Our lab works with collaborators at Harvard’s Department of Radiology to make brain image data visually comprehensible. The goal is to support diagnosis, by revealing pathology in a brain, and intervention, by depicting possible outcomes of interventions.

Our lab works with collaborators at ORNL and elsewhere to visualize output of computational simulations in biology, chemistry, and physics. The goal is to develop techniques to make comprehensible imagery of petascale, large-dimensional, and uncertain datasets.

I’m broadly interested in formal specifications and analyses that resonate with end-users. I have projects on user-friendly policy analysis, creating formal specifications from the varied informal and diagrammatic notations in protocol documentation, and deriving software libraries from declarative specifications. I also work on a nontrivial outreach program for early computing education, with a current focus on middle-school students. This project, Bootstrap, exploits animations programming to reinforce core algebra skills. We work on programming environments for Bootstrap from a variety of perspectives (ie, human factors, software architecture, and education).

I am especially seeking post-docs in the fields of gesture recognition, information visualization, information retrieval, distributed services, and ubiquitous computing to participate in interdisciplinary teams.
Mixed-initiative information composition integrates searching, browsing, organizing, modeling, and visualizing multimodal information from heterogeneous sources to support learning and thinking. Exposure to diverse relevant information optimizes cognition and helps overcome fixation on preconceptions, stimulating innovation. We previously developed a method for measuring emergence in information discovery tasks to show in experiments that using composition to represent information collections increases emergence. Current research integrates multitouch surface computing, diagramming, and mixed-initiative information composition to cyber-enable design emergence.
Location-aware non-mimetic simulation games for teaching team coordination are based on ethnographic investigation of fire emergency response. We introduce non-mimetic simulation to describe environments that model contextualized human task operations, emphasizing the structure of human communication and coordination, while abstracting out physical characteristics of an environment. Non-mimetic simulation focuses simulation resources on goal-directed operational characteristics of task performance, such as information flows.
I am deeply committed to fostering the next generation of creative and expressive computer scientists, ethnographers, designers, and artists, who will take leadership in the conceptualization, research, and development of systems, media, and evaluation methods. My long term objective is to use computing to elevate creativity, expression, and participation in human life.

The work in the Social and Technological Action Research Group (STAR) is largely focused on understanding socio-technical phenomena and creating interventions and solutions, both in policy and in technology, to make the world a better place. We work in human-computer interaction (HCI), computer supported cooperative work (CSCW), mobile and ubiquitous computing (ubicomp), medical informatics, educational technology, assistive technology, and privacy. That last one comes up a lot, because in the other work we do, we often wind up collecting a lot of data either as part of human record-keeping practices for health and education or because of automated capture and access and sensing systems.

In our group, we focus on projects that address real human needs and challenges. For example, we currently are working on projects to support the communication needs of children with autism, to understand how people respond to and comprehend recording and tracking technologies that are becoming so prevalent in the world today, and to support and assess the adoption of electronic and personal health records in clinical and non-clinical settings. This kind of work means drawing on computational, social science, and design skills. If you are interested in designing, creating, and/or studying the use of information and communication technologies to help make the world a better place for the future, our group is a good place for you to be.

We work as a team, and researchers are expected to be able to work independently but also to support one another and make sure everyone can be successful. We are also affiliated with the Laboratory for Ubiquitous Computing and Interaction and students and post-doctoral fellows are encouraged to work with other faculty members within that lab and across the department. Our work is generously funded by an NSF CAREER award, AutismSpeaks Innovative Technology Award, the NIH, and support from other sponsors such as Microsoft, Nokia, and the National Center for Women and Information Technology.

My main interests are in accessibility technology that can be used to enable persons with disabilities to have access to computers, the web, education, and the workplace. Projects include the WebInSight, making the web more accessible by automatically or with human assistance improving web page accessibility; Deaf and Hard of Hearing Cyber-Community, making education more accessible to deaf and hard of hearing students; and MobileAccessibility, transforming cell phones into accessibility devices for people who are blind or have low vision. I am open to any new projects that a research fellow would want to work on in the accessibility space.

I am interested in all aspects of programming language research and research on program design.

My web page explains my current projects but I am open to other ideas.

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.

My research interest lies in understanding and advancing the role of design, coordination, and education in software engineering. I am particularly interested in the following three research directions:

* Understanding software designers in action: we have begun collecting videos of software designers designing, and are curious about how they actually do so, what kinds of effective strategies they use, how software design relates to other design disciplines, etc.

* Sketching & software design: we are interested in creating software sketch tools that better support software designers in the creative and exploratory activity that is design.

* Coordination in software engineering: we are interested in how various kinds of awareness displays built using different metaphors can assist software developers in their day-to-day coordination activities.

Research methods and approaches cross CSCW, SE, and HCI boundaries, and may vary from field studies, to experiments, to tool building, etc.

Current major interest is integrating clouds, grids and high performance multicore clusters for data-intensive science such as understanding data from next generation gene sequencers, particle accelerators, polar expeditions and SAR satellites. Novel algorithms, sophisticated performance analysis and new programming models are aspects of this work. I use smartphones forming collaborative sensor nets and new educational technology from Web 2.0. I work extensively on bringing benefits of Cyberinfrastructure to Minority Serving Institutions. Computational Science and Informatics as interdisciplinary education approaches are other interests.

We are working on ways for students (and others) to collaborate effectively on projects, by designing a reward system that encourages them to make creative contributions. In the realm of education, this means that students will help faculty “co-produce” a course, by creating resources to help students learn the material–exercises, videos, wiki textbooks, etc.. To make this process scalable, it relies heavily on several kinds of peer review. Quality control is under the control of a reputation system, which attempts to insure that only careful reviews are weighted heavily in the assessment process.

We have released a dynamic verifier for MPI called ISP and one for Pthreads called Inspect. We are developing dynamic verifiers for MCAPI and are interested in similar tools for CUDA/OpenCL. Handling combinations of concurrency models/libraries is of interest. This focus stems from the need to provide safety-nets to programmers while they write and optimize concurrent programs. Pedagogy needs to be dramatically impacted by offering verifiers that provide formal coverage guarantees (e.g. no deadlocks for classes of inputs), and also improving programming productivity. Sound downscaling of large concurrent systems to put them within reach of formal analysis is of interest, as are other methods that reduce verification effort (e.g., dynamic partial order reduction, symmetry, data independence). We are keenly interested in employing static analysis and decision procedures increasingly in conjunction with dynamic analysis. We seek and thrive from industrial collaborations, and love to involve undergraduates in research and tool development for concurrency.