Ultimately saying, I am interested in how the brain works. Also I am studying about how to model the brain function and how to use the knowledge of the brain to build intelligent agents.

I am seeking a post-doc to serve as the software systems technical lead on a two-year NIH project concerning computer support for medical response in disasters (see abstract below), called WIISARD SAGE. We have a large multi-disciplinary team comprising computer scientists, emergency physicians, and computer engineers. As part of leading the software research effort, the post doc would work with several graduate students and programmers who are assisting in the effort, as well as coordinate design and evaluation efforts with the project’s medical lead. This would be an ideal project for a software engineering or systems researcher to become trained in the systems aspects of disaster informatics.

Project Abstract
———————-
Every year, natural and human-caused caused disasters in the form of hurricanes, earthquakes, and infrastructure failures put the health of millions of US citizens at risk. The proposed research project will investigate how to scale the capabilities of existing prototype mobile wireless information systems for medical response in disasters to increase the quality of care in these wide-scale, chaotic disasters. Advances will include the support of multi-site workflow in loosely networked conditions, self-adaptive configuration and scaling to accommodate the gradual arrival of first-responder teams, and the improved function and transparency of the system in the harsh and changing conditions that can compromise network connectivity.

My research lies in the areas of Information Assurance, Applied Cryptography and Network Security. I build systems mainly, but I enjoy ellegant foundations, especially if of the very rare practical variety.

Irfan Essa works in the areas of Computer Vision, Computer Graphics, Computational Perception, Robotics and Computer Animation, with potential impact on Video Analysis and Production (e.g., Computational Photography, Image-based Modeling and Rendering, etc.) Human Computer Interaction, and Artificial Intelligence research. Specifically, he is interested in the analysis, interpretation, authoring, and synthesis (of video), with the goals of building aware environments, recognizing, modeling human activities, and behaviors, and developing dynamic and generative representations of time-varying streams.

He is motivated to build smart intelligent machines that can interact with people. He is also interested in machines that can handle large amounts of media and wants leverage social networks to build systems for large groups of people to interact and create smart media.

Computer Graphics and Visualization, Biomedical Imaging and Computer Vision, Geometric and Physics-based Modeling, Virtual Reality and Human-Computer Interaction, Computer Animation and Simulation.

Machine learning, meta-learning, artificial intelligence, pattern recognition applied to problems in physics and astronomy.

Scott Mainwaring has a broad and eclectic background in computer, cognitive, and social sciences. For the last 15 years, Scott has applied his skills in ethnographic inquiry and analysis to the revolutionary potential for information and computing technologies in everyday life. At Interval Research Corporation, where he was a postdoc and later staff researcher, Scott collaborated with designers, business planners, engineers, and documentary filmmakers to design domesticated media spaces, virtual worlds, ICT-augmented television, and services for the Baby Boom generation. At Intel, Scott explores the relationships between individuals and the systems in which they find themselves embedded. For the past several years, Scott has been researching emerging technologies of digital money and financial inclusion and how they play upon money’s emotional, cultural, and religious meanings. His current focus is on the processes creating and disrupting “middle class” consumers in both developed and developing countries, and how ICTs are implicated in them. Scott has an A.B. in computer science from Harvard University and a PhD in cognitive psychology from Stanford University.

There are two areas of interest:

1) Database Middleware – Techniques for fault-tolerance query processing in mobile environments, where data sources themselves are mobile hosts.

2) Energy-Efficient, Data Intensive Data Management for the Clouds – Novel DBMS architectures designed for Cloud environments, that can scale to thousands of hosts and minimize the amount of energy their consume during query processing.

Biological sequence analysis, multiple sequence alignment, genome alignment, motif discovery, protein and RNA secondary structure, DNA sequencing, genome rearrangements, inverse parametric optimization, algorithm engineering.

I have worked in the area of high performance for over 10 years with an additional 4 years in the area of art, humanities and computing. I am interested in bridging these areas by using the arts and popular culture to increase digital literacy in the in under served populations.

Wireless Systems and Networks, Energy efficient algorithms and protocols, Resource management schemes, Medium Access Control, Cognitive Networking, Information Theory and Applications, cognition in network systems, distributed systems, stochastic control, mobile ad hoc networks, wireless mesh networks, cellular systems research. Emergency response networking, tele-medicince applications of networking.

Broadly speaking, my research interests are in computer networks and their security. I am currently interested in understanding how Internet fraudsters provision cybercrime infrastructures. Toward this goal, I conduct large-scale Internet measurements involving many aspects of infrastructure provisioning, including the DNS. Analyzing and storing vast quantities of data is a natural side effect of such measurements.

My general research area includes wireless networking and systems, mobile computing and multimedia computing. I am also interested in security and distributed systems. My current research is on cognitive radios & networking, dynamic spectrum sharing and auctions, with a particular focus on improving network reliability and robustness.

cognitive mobile networks, machine learning in wireless networks, autonomous cognitive networking, distributed cognitive networking, cognitive wireless networks, cognitive radio, cognitive radio networks.

My broad research interests are in speech and language processing, with a slant toward combining statistical and machine learning techniques with knowledge about language structure from linguistics and speech science.

My recent work involves several topics:

- Models of the articulators (lips, tongue, etc.) for speech recognition (especially for pronunciation modeling in conversational speech), implemented as graphical models.

- Audio-visual speech recognition, using dynamic Bayesian networks to account for the apparent asynchrony between the audio and visual streams.

- Multi-view learning of feature spaces for various speech tasks, using additional views at training time such as video or articulatory measurements.

- Additional modalities in speech processing besides audio and video. For example, one promising source of information appears to be from ultrasonic “microphones”, in which the motion of the articulators is detected via a Doppler shift in a reflected ultrasonic signal.

In addition to these, I am also interested in exploring similarity-based techniques for speech applications and model-based speech processing (such as denoising or reconstruction of degraded signals).

A note about TTI-Chicago: It is an independent institute dedicated to basic research and graduate education in computer science. We are located on the U. of Chicago campus, but are an independent institute with our own PhD program. The main current areas of research at TTI are machine learning, artificial intelligence and related applications (vision, robotics, speech, natural language), theory of computation, programming languages, computational biology, and scientific computing.

I am interested in the biomechanics of locomotion through fluids, with a special focus of mechanics of fish propulsion. In my lab we use many different experimental techniques to understand the production of locomotor forces by freely swimming fishes, and also a variety of biorobotic systems to study fish fin and body function. My lab web site (http://www.people.fas.harvard.edu/~glauder/) and our YouTube Channel (http://www.youtube.com/user/LauderLab) have many videos and all recent reprints.

The Community Grids Laboratory, led by Prof. Geoffrey Fox, is looking for researchers to lead projects in Cloud computing (both systems design and large scale parallel application development), parallel computing, message-oriented middleware, and experience with streaming systems of all types (including sensor Webs and audio-video systems).

For a snapshot of lab activities, see our presentations and publications at http://grids.ucs.indiana.edu/ptliupages/presentations and http://grids.ucs.indiana.edu/ptliupages/publications/. We have a distinguished publication and funding record in parallel computing, Cloud computing, the application of Web technologies to scientific problems, and publish/subscribe systems.

The Community Grids Lab is part of the recently refunded Pervasive Technology Institute. We work closely with the Indiana University Research Technologies division, which provides world-class scientific computing infrastructure. Lab facilities are located in the IU’s new Incubator facility.

High performance computing, MPI, generic programming, C++, scientific computing, numerical analysis, parallel programming, large-scale systems, computational photography

My current research interests include : Network management, Configuration management, Network measurements, Network Security, Routing and Data plane interactions, Traffic analysis, Network data mining, Performance analysis and troubleshooting

Recent research papers are at : www.research.att.com/~sen

My research interests include automatic performance analysis, which includes identification and tuning of performance bottleneck. My current focus is on developing analysis and tooling for Java enterprise applications running on multi-core systems.

The most pressing and urgent problem in software development is the creation of software on which we can rely to perform as intended. Given how ubiquitous software is in every field of human endeavor, this is one of the most important problems facing mankind. My research focuses on the development of software systems for distributed and high assurance applications. Part of this work relates to the formal specification of software properties. Formal specifications can be used by a variety of software tools for creating and verifying software. These tools include model checkers, theorem provers, runtime monitors, and program synthesis systems. Formal specifications can be used to identify conflicting requirements, manage change in requirements (pre- and post-deployment), and detect errors during software execution.

I am engaged in the application of software engineering technology to real world problems, namely the development of application software for use by scientists and engineers. The goals of the development of this set of applications are two-fold: first, it is my intent to provide software support to important research, research that might not be possible without the availability of reliable, trustworthy software. As such, much of the work is multidisciplinary. Second, the development of production software provides numerous examples against which to test the cost-effectiveness of industrial software engineering approaches. Ideas on improving the reliability and reducing the cost of software abound; however, few are used in practice, in part because their efficacy remains undemonstrated. By applying techniques and practices to real-world software projects, we are testing the applicability and cost-effectiveness of these techniques and training a cohort of software engineers who can make reasoned decisions about these techniques in industrial practice.

Most prominent of this work is the development of the software currently in use by the space scientists in the analysis of data from the NASA Cassini mission to Saturn. Software developed for this mission aids in mission planning and rapid opportunity analysis as well as image analysis from the ISS, CIRS, and VIMS instruments on Cassini. The research group has investigated and developed a number of software refactorings that are used to migrate procedural IDL code to object-oriented IDL code.

Other applications under development include the PROSPEC property specification tool, which guides domain experts in the development of formal specifications for use by formal software analysis tools. Aligned with this is the development of a framework for model-checker based testing of formal specifications and the development of mechanisms for the generation of specifications in LTL. The PROSPEC work includes porting the software to the Eclipse platform and providing visual feedback for validation of the resulting specifications.

In the fall of 2008, I began working with Craig Tweedie of the Systems Ecology Laboratory in the Department of Biology at UTEP. This work will result in a system that allows climate researchers to access data from a network of sensors. A novel part of this system is the automated data quality flagging that identifies anomalous data on upload

cooperative control, distributed algorithms, learning, optimization, nonlinear control, geometric control

Our lab includes advaced research in the areas of computer graphics and a broad array of visual computing topics from input sensors to amatuer content creation (3D model extraction from photos etc), to procedural representations of avatars and animations of same, there are some elements of Video and Image processing using complex statistical algorithms and explorations of challenges / new application scenarios made possible by the evolution of Mobile Internet Devices and the sensors that are expected to be attached, also Mobile Augmented Reality whereby such MIDs can add value to the experience by leveraging the sensor inputs along with direct connection to the internet.

My research interests include concurrent/distributed systems, reflective and adaptive middleware, multimedia systems and applications, middleware for mobile applications, formal reasoning of distributed systems.

Interested in against-conventional-wisdom approaches to solve the most challenging problems in computer architecture. Currently am working on a novel execution model to program sequentially (i.e.,deterministic execution with no synchronization constructs), but run programs in parallel, on stock hardware. If you are interested in going against the tide of conventional wisdom in attacking one of the most challenging problems facing the computer industry, consider coming to Wisconsin.

My research areas include auditory neuroscience, music psychology and dynamical systems theory. My interdisciplinary research combines behavioral experimentation, neurophysiology, and neuroimaging with nonlinear dynamical systems modeling, to gain a deeper understanding of the neural underpinnings of musical experience. In my lab, we create computer models to explain the structure of music, and its interaction with brain dynamics. Current research projects include the perception of pitch, the perception of tonality, the perception of rhythm, auditory attention, communication of affect and emotion, and the neural basis of song.

My work at Google focuses on improving the programmability and performance of web applications delivered over the internet. Recent years have seen an explosion in size and scope of web applications to the extent that they are now straining the capabilities of today’s web execution frameworks. I am investigating the evolution of these frameworks to better handle greater client-side compute requirements, scalability, programmability, and security.

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.

At Google, Sergey works on developing data management solutions for web-scale data sets.

Cloud Services Composition

Advances in Cloud Computing have enabled service providers to offer business services in an economic way, and provided businesses customers incentives to access and outsource functions to cloud services. In most cases, a given cloud service covers only part of functions needed by a business, and therefore, businesses need to use a number of services. One major challenge to ensure seamless function of the business is the integration, composition and orchestration of these services. There has been extensive prior work on automated approaches for service integration and composition in the context of Web services. However, no industrial strength approach addressing or facilitating this problem has emerged.

In the context of a research project in HP Labs, we are developing technology to enable a service marketplace for service providers to offer services, and for service customers to find, compose and integrate services. We welcome a motivated, sharp and self-starter postdoctoral fellow with strong background in the theory and practice of service oriented computing, service compositions, business processes to work on the problem of composition of business services offered in the cloud. The candidate should be capable of formulating the research problem, proposing novel ideas and implementing ideas into prototypes and should demonstrate a strong publication record. HP Labs is located in Palo Alto, CA (SF Bay area) which offers a vibrating and active academic and industry environment.

Coding theory, distance geometry, combinatorics, cryptography

In robotics we are interested in motion planning with emphasis on high-dimensional systems and kinodynamic planning, 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 such as MicroElectroMechanical Systems.

In computational structural biology and bioinformatics we develop computational 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 capture, represent and exploit relevant molecular motion.

Topic: Industrial Strength Cloud Services Composition

Advances in Cloud Computing have enabled service providers to offer business services widely, and in a more economic way, and given businesses customers more incentives to access and outsource functions to cloud services. In most cases, a cloud service covers only part of functions needed by a business, and therefore, businesses need to use a number of services. One major challenge to ensure seamless function of the business is the integration, composition and orchestration of these services. There has been extensive prior work on automated approaches for service integration and composition in the context of Web services. However, no industrial strength approach addressing or facilitating this problem has emerged.

In the context of a research project in HP Labs, we aim at developing a service marketplace for service providers to offer cloud services, and for customers to find, compose and integrate services. We welcome a motivated, sharp and self-starter postdoctoral fellow with strong background in the theory and practice of software engineering, service oriented computing, service compositions, business processes to work on the problem of composition of business services offered in the cloud. The candidate should be capable of formulating the research problem, proposing novel ideas and implementing ideas into prototypes and should demonstrate a strong publication record. HP Labs is located in Palo Alto, CA (SF Bay area) which is a vibrating and active academic and industry environment.

My current research focuses on various aspects of social computing. My work has spans topics such as collaborative tagging for inferring user interests/expertise and indexing rich media content such as audio and video, communication dynamics in social networks, inferring interestingness of conversations around media objects such as YouTube videos, social synchrony in social networks, privacy and awareness. I am also starting to study microblogging.

I work in the areas of computational electronics and quantum transport theory. My group uses a variery of numerical techniques to address the transport of charge and heat in semiconductor nanostructures. Some of our recent projects include:

(1) Electronic and thermal properties of nanostructures. Nanostructured thermoelectrics
(2) Monte Carlo simulation of quantum cascade lasers
(3) Decoherence in nanostructures
(4) Global modeling of carrier-field dynamics in conductive media using EMC/FDTD
(5) Flexible electronic systems (e.g. semiconductor membranes and ribbons)
(6) Solid-state-based quantum information processing. Spintronics

For a detailed description of current and recent projects, please visit http://homepages.cae.wisc.edu/~knezevic/

I work in the broad area of computer systems. My current interests are virtual machines, deterministic replay, fault tolerance, and computer security. I am also starting to think about how to apply information and communication technology to help people in developing countries.

Norm’s research interests include implications of emerging nanophotonic technology on computer systems, low-latency high-bandwidth networking for cluster computing, heterogeneous chip multiprocessor architectures, and blade system architectures.

I am interested in designing and implementing large-scale distributed systems that are robust and easy to write applications against. I have worked on a variety of projects including a distributed persistent object store, a secure distributed serverless file system using Byzantine fault tolerance, diagnostics in wireless networking, object-relational mapping framework, and a distributed auto-partitioning lease manager for datacenter servers – the last two pieces of work shipped as part of commercial products/large-scale online services.

I seek to develop programming systems, i.e., languages, libraries, compilers, and development tools and environments, that are (a) natural and easy to use, (b) efficient to run (particularly over very large data and many machines), and (c) actually used in practice by real developers getting real work done. Some of my recent work at Google includes libraries and run-time systems supporting easy yet efficient massively data-parallel pipeline computations, and data synchronization infrastructure for easier development and deployment of web-based applications.

My research is focused on navigating and positioning objects in 2d and 3d virtual environments. The research has developed general gesturing techniques, a new mouse driver for desktop environments, and modeled the effectiveness of users to locate themselves in 3d environments and position objects in 2d. The laboratory has a stereo visor for augmented and immersive environments, magnetic and optical trackers, and grasping gloves.

Future research is extending gesturing techniques for navigating and specifying objects or regions in multidimensional virtual environments using multimedia virtual environments. The primary application area is studying and interrogating multidimensional scientific data. We intend to learn the limitations of computer users to navigate abstract environment and improve the navigation and positioning techniques by human performance modeling.

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.

Fault Tolerance, Reliability, Computer Architecture, Power management, Performance and power analysis, Soft Errors, System Design, Low power circuits, system design methods

My research interest lies in the intersection of high performance computing, combinatorial scientific computing and biomedical informatics.

Cryptography and other topics in theoretical computer science related to computational complexity.

I am interested in innovative research which spans compiler/architecture boundary
particularly alternative forms of parallelism, including memory-level and instruction level parallelism. Current research projects include a new program representation which permits unrestricted code motion, compiler algorithms for optimizations on this representation as well as new micro-architecture designs capable of directly executing this representation. The representation has its roots in data-flow, demand driven and instruction-level parallelism. I am also interested in domain specif?c languages particularly automatic generation of micro-architecture simulators.

The focus of our research consists of the development of locality analysis for single- and multi-threaded applications to enable the prediction of the resource requirements of those applications. Our research will apply new memory locality models to manage the cache and bandwidth requirements for single–threaded applications, and to manage remote memory access caching in addition to on-chip cache requirements for multi-threaded applications. Specifically, our research will examine locality models for predicting the memory behavior of single-threaded scientific applications and multi-threaded Partitioned Global Address Space (PGAS) applications written in Unified Parallel C (UPC).

A main focus of my research concerns the learning and structure of Boolean functions and their representations. My interests in this area include problems in learning, recognition, minimization, and certificate complexity. I am especially interested in problems related to DNF and junta learning.

In addition to doing purely theoretical work, I enjoy collaborating with practitioners. I am currently working with researchers in databases, applied machine learning, and protein engineering. My work with them involves the solution of theoretical problems that arise in applied work.

Topics of my recent papers include learning juntas given access to examples from multiple product distributions, algorithms for maximizing throughput of queries in parallel databases, and the complexity of truth-table DNF minimization.

• 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).

Power-aware scalability spanning parallel algorithms to advanced architectures. Sparsity and data-intensive scalable computing, Applications to computational discovery of new materials and metagenomics; Performance modeling of cloud computing.

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.

My research in interests include image/video analysis (including texture and shape analysis, segmentation, registration), multimedia databases and data mining (feature extraction, content based access, high dimensional indexing and similarity search), steganography (data hiding in images and video, and their detection), and signal/image processing for bio-informatics. I direct the NSF/ITR funded Bio-Image Informatics Center and NSF sponsered IGERT program on Interactive Digital Multimedia. I am also associated with the interdisciplinary Multimedia Arts and Technology program and the Computer Science Department. The Vision Researh Lab web page gives more details about the current projects in my group.

My research interests are in storage systems, distributed computing, and distributed systems.

Interested in all areas of computer security, especially software and systems security. I am *actively* looking for a postdoc (and will actively work with them!). Currently working on formally reasoning about binary (executable) code, including applications such as automated exploit generation, and techniques such as efficient symbolic execution. Also working on cryptographic primitives and implementations for achieving anonymity, and work in very large scale applications of software security (e.g., analyzing millions of malware programs at a time in order to classify and categorize them).

My current research focuses on the following three main areas:
1. QoS-sensitive wireless networks: sensing and adaptation in cognitive radio networks, mesh networks, and sensor networks.
2. Deeply embedded and/or cyber-physical systems: co-design of cyber and physical systems with mutually understandable abstractions, resource usage monitoring and management for timelienss and other QoS requirements
3. Security and privacy in computing and networking systems: detection and removal of bots, protection of application privacy/secrecy in untrusted environments, self-securing handsets.
4. Resource management and QoS adaptation in large-scale virtualizaed data centers

My research focuses on cryptography and its applications to addressing
issues of security and privacy in distributed systems. Recent research projects
include: cryptographic constructions to support a novel network architecture that
would enhance the current Internet with strong guarantees of security; RFID
authentication protocols; and a system for on-line elections and voting by small and
medium-sized constituencies.

For more information, see http://www.cs.stevens.edu/~nicolosi/ .

My research interests are in Cryptography and Information Security. Please see my website for more information:

http://www-cs.ccny.cuny.edu/~fazio/

Signal processing, wireless communications, sensor networks

For a description of my research interests and a complete list of my publications, please see my personal research web page (listed above).

The investigation of an open source distributed cloud computing platform (AppScale) and its support infrastructure to identify new techniques that make it easier for a broad population of users to design, develop, debug, and deploy creative and scalable applications on remote resources.

Please see my home page and publications.

My research interests focus on several areas related to data management for large-scale, distributed scientific applications. These interests include examining the relationship between data management systems and workflow management systems to improve the execution of data-intensive scientific applications; the use of policies and policy engines to manage distributed scientific data sets, including policy-driven data replication; the design and evaluation of tools for management of large, replicated data sets in real-world scientific environments; and the exploration of peer-to-peer techniques for organizing distributed catalogs for replica management and information management. I manage research and development projects related to data management for several large scientific collaborations, including the Earth System Grid, which provides support for the next generation of climate science; the Laser Interferometer Gravitational Wave Observatory project, which is working to detect gravitational waves; the Biomedical Informatics Research Network (BIRN) Coordinating Center, which provides support to neuroscience groups for collaboration and data sharing; and the Center for Health Informatics (CHI), which provides infrastructure for secure medical data sharing for clinical and research applications.

My current research is primarily focussed on algorithms and analysis of communication networks, wherein my current focus is on two newly emerging areas: Network Economics and Network Game Theory. “Network Economics” studies problems in networks that arise due to economic issues in networks. It is being realized that merely distributed optimization in networks can lead to sub-optimal outcomes since many networks (such as the Internet) are too large to be controlled by a single entity, and moreover each entity has its own economic objectives. Thus, future resource allocation algorithms and network protocols must be cognizant of the distributed and multi-objective nature of the network entities.
“Network Game Theory” studies problems that arise in multi-player games where the players are connected through a (social or communication) network. Typical problems include routing and congestion games, to reputation games in network security systems. There are problems of both (interaction) mechanism design such as auction design, as well as cooperative and non-cooperative game analysis.
There is overlap between the two areas along with traditional microeconomics and classical, computational and algorithmic game theory. Some of the mathematical tools used are real analysis and topology, fixed point theory, optimization, probability and approximation algorithms. I also have a strong interest in Stochastic Systems, their Modeling, Optimization and Control. Of particular interest is using and developing statistical learning theory and techniques for stochastic dynamical systems (such as Markov decision and Markov game models, hence my interest in machine learning).

My research applies Discrete Control Theory to dynamic failure avoidance for concurrent software. A major goal of my ongoing collaboration with colleagues at HP Labs and the University of Michigan is to refine and extend our dynamic deadlock avoidance methodology by incorporating more sophisticated static analyses, e.g., path-sensitive analysis and pointer analysis. See our papers in POPL 2009 and OSDI 2008 for an overview of this project.

The primary goal of my research is to help people make sense of overwhelming amounts of information by combining the flexibility of higher-order cognition, the strengths of social collaboration, and the power of machine learning and visualization. My current research uses technology to help large groups of people collaborate to produce knowledge and solve problems that exceed an individual’s cognitive capacity. To this end I have pursued two complementary lines of research: first, investigating how to optimally harness the “wisdom of crowds” in social collaborative systems such as Wikipedia; and second, building machine learning and visualization-based techniques to increase the effectiveness of these systems.

My research focuses mainly on enabling the efficient and reliable execution of scientific workflows in distributed environments. In my group at ISI, we have been working with a number researchers in variety of science domains, including astronomy, biology, earthquake science, physics, and others and developing technologies to support their large-scale science. As a result we built a workflow management system, Pegasus: http://pegasus.isi.edu and related technologies including resource provisioning capabilities.
Many scientific disciplines are using workflow technologies to manage their complex analysis. Workflows provide a representation of complex analyses composed of heterogeneous models designed by groups of scientists. At the same time, workflows have also become a useful representation that is used to manage the execution of large-scale computations. This representation not only facilitates overall creation and management of the computation but also builds a foundation upon which results can be validated and shared. Since workflows formally describe the sequence of computational and data management tasks, it is easy to trace back how particular results were derived by examining the associated provenance trail.
In order to use the system, the scientist needs to describe the workflow at a high-level, capturing the computations involved and the data that need to be processed. This description is usually independent of the underlying cyberinfrastructure. The workflow along with information about the execution environment (including data and computational resources) is used by Pegasus to generate an executable workflow and to run it in an efficient and reliable fashion.
Within Pegasus, the Pegasus mapper finds the appropriate software and computational resources where the execution can take place as well as finding copies of the data indicated in the workflow instance. The mapping process can also involve workflow restructuring geared towards optimizing the overall workflow performance as well as workflow transformation geared towards data management and provenance information generation. The result of the mapping process is an executable workflow, which can be executed by a workflow engine that follows the dependencies defined in the workflow and executes the activities defined in the workflow nodes. DAGMan, the workflow engine of Pegasus relies on the resources (compute, storage, and network) defined in the workflow to perform the necessary actions. As part of the execution, data are generated along with their associated metadata and any provenance information that is collected.
A part of our system development we conduct research in the area of workflow scheduling, resource provisioning, data management, cloud computing, and others.
We develop novel algorithms to schedule jobs onto distributed resources, to estimate the resource needs of applications and provision resources accordingly. Through simulation and experimentation we evaluate the applicability and costs of cloud computing for science applications.
Much of our research focus is also on scalability and robustness of our system. In one scientific workflow in earthquake science, we need to manage approximately a million of individual jobs.

I am interested in understanding 3D properties of visual scenes from 2D images and videos, and in active learning approaches to this problem. In particular, I would like to understand how a use of mobile visual platforms (robots with cameras) can help us collect better training data for statistical learning algorithms that address the problem of 3D scene recovery from 2D imagery.

I am also interested in bottom-up methods for parsing and recognition of motion in videos, with primary focus on articulated tracking, such as hand motion understanding.

More broadly I am interested in statistical learning methods for example-based learning and inference, and semi-supervised learning.

TTI-Chicago is an independent research institute dedicated to basic research and graduate education in computer science. We are located on the U. of Chicago campus, but are an independent organization with our own PhD program. We are currently primarily focused on machine learning, artificial intelligence and related applications (vision, robotics, speech, natural language), theory of computation, programming language, and scientific computing (signal processing, computational biology).

My research focuses on mining and modeling large social and information networks, their evolution, and spread of information, influence and viruses over them. Problems I investigate are motivated by large scale data, the Web and other on-line media. I also do work on text mining, large scale sensor placement problems, and applications of machine learning.

I am interested in extending methods from mathematical analysis (such as measure theory, fractal dimensions, ergodic theory, and Fourier analysis) to make them into suitable tools for attacking problems in the theory of computing (especially structure of complexity classes, algorithmic information theory, data compression, prediction, and inherently spatial models of computation).

cognitive radio networks, mobile social networks, disruption tolerant networks, network security

My group conducts research in modeling, animation, and graphics systems. In 3D modeling, we are developing novel interfaces and algorithms that help novice modelers in creating high-quality 3D objects and scenes. We study the motivations and processes of novice modelers and develop tools that make the modeling process more tractable. In animation, we investigate data-driven animation and its applications in interpersonal communication. Modern machine learning techniques are instrumental in our work on modeling and synthesizing animation. In graphics systems, we investigate the applications of image-based and volumetric approaches to the rendering of massive environments.

My research interests are in the area of asynchronous (i.e. clockless) and mixed-timed circuits and systems.

Specifically, I am interested in design and test of asynchronous systems, including: (i) high-level specification and translation; (ii) performance analysis; (iii) system-level optimization, including bottleneck detection and alleviation; (iv) mapping to asynchronous pipelined circuits; and (v) test and testability issues.

In addition to pure asynchronous systems, I am interested in mixed-timed systems as well, including globally-asynchronous locally-synchronous systems (GALS), latency-insensitive design, elastic systems (both synchronous and asynchronous), and on-chip-networks (NOCs).

My research group actively pursues work at various levels of abstraction: from circuit level (asynchronous pipeline circuits), to microarchitecture level, to system level. The work also targets several application areas in high-speed and low-power computing.

A particular area of research interest is mobile low-power graphics hardware. In collaboration with Prof. Anselmo Lastra, we are developing architectural techniques for ultra-low-power graphics, suitable for handheld gaming devices, cell phones, PDAs, etc. An active line of investigation is to dynamically trade off solution quality for energy savings when energy conservation is critical. This project also targets several levels of design abstraction: circuit, microarchitecture, system, memory, and software.

Finally, I am interested in exploring the application of asynchronous design techniques for the next-generation silicon and non-silicon emerging technologies, such as nano, quantum and biologically-inspired computing.

My research group focuses on developing automatic analyses of programs to support software testing (recently focusing on web applications), software developer search of source code during maintenance (concern location), optimization for improved performance for parallel architectures, debugging, program understanding and other software developer tools. We use machine learning, data mining, and manual analysis of thousands of large software systems to guide the development of our analyses, and evaluate our techniques through solid experimental study, human subjects when appropriate, and statistical analyses. The research group involves collaborations with professors within the university as well as collaborators at other universities. The research lab includes PhD, master’s and very good undergraduate student researchers.

Current research topics include: profile-guided compilation, high-ILP microarchitectures, GPGPUs, architectural features for security, IO performance and modeling, power modeling, virtualization, workload characterization, memory hierarchy design, embedded systems design, digital signal processors and software testing.

My current research interests include:
* Software model checking: Using symbolic or explicit state model checking techniques to verify (or falsify) software systems.
* String analysis: Automata-based symbolic analysis for detecting and preventing vulnerabilities that relate to string manipulation.
* Analysis and verification of web software: Application of automated verification techniques to interactive web applications and web services.
* Design for verification: Investigating new ways of constructing software to facilitate effective automated verification.

Analyzing Web software:

I am interested in VLSI design automation area generally, with specific focus in the areas of system level verification and simulation. I am also interested in static circuit timing, statistical static timing, circuit tuning and optimization.

Current research interests: generation of natural language and nonverbal behavior; conversational grounding in dialogue systems, rapport in human-computer interaction, modeling embodied conversational agent behavior on the basis of corpora of human-human interaction (markov models, game theory, etc.); human figure animation; interaction between real objects and virtual humans (systems that can handle sensors, natural language & graphics); virtual peer technologies to teach literacy and science skills to children, technologies for autism

Optical networks and Wavelength Division Multiplexing (WDM), Network Security and Secure Group Communications (SGC), Wireless sensor networks (WSNs) and environmental sensing,
P2P multimedia streaming technologies.

One of my recent research thrusts is on uncovering fundamental limits and algorithms for interactive and secure information processing in networks using tools from network information theory and communication complexity theory. In parallel I am also exploring information processing in visual networks using tools from statistical learning theory and multidimensional signal processing.

The research at the USC Interaction Lab, part of the USC Robotics Lab and the USC Center for Robotics and Embedded Systems is focused on socially assistive robotics: developing methods and algorithms that enable robots to aid users through social non-physical interaction. We are inspired by the dual goals of 1) gaining novel insights into human behavior and cognition through human-machine interaction and 2) developing robotic systems capable of providing personalized assistance in convalescence, rehabilitation, training, and education. Our research addresses challenges of embodiment, activity and social monitoring, human-robot interaction, and user adaptation. We are developing technology-assisted intervention methods that use intelligent human-robot interaction (HRI), control, and learning in complex, dynamic, and uncertain environments by integrating multi-modal perception, communication, and interaction with users. To address the inherently multidisciplinary challenges of this research area, our work draws on theories, models, and collaborations from neuroscience, cognitive science, social science, health sciences, and education. We validate our approaches with user groups of stroke patients, children with autism spectrum disorders, and individual suffering from dementia/Alzheimer’s Disease.

Jorge Cortés is an Associate Professor with the Department of Mechanical and Aerospace Engineering at the University of California, San Diego. He received the Licenciatura degree in mathematics from the Universidad de Zaragoza, Spain, in 1997, and the Ph.D. degree in engineering mathematics from the Universidad Carlos III de Madrid, Spain, in 2001. He held postdoctoral positions at the Systems, Signals and Control Department of the University of Twente in 2002 and at the Coordinated Science Laboratory of the University of Illinois at Urbana-Champaign from 2002 to 2004. He was an Assistant Professor with the Department of Applied Mathematics and Statistics at the University of California, Santa Cruz from 2004 to 2007. He received a NSF CAREER award in 2006. He is the author of the book Geometric, Control and Numerical Aspects of Nonholonomic Systems (New York: Springer-Verlag, 2002) and the recipient of the 2006 Spanish Society of Applied Mathematics Young Researcher Prize. He currently serves in the Editorial Board of Systems and Control Letters and the European Journal of Control and in the Conference Editorial Board of the IEEE Control Systems Society.

My area of research is to develop computational methods that will impact the way scientists analyze data from biological and medical genomics experiments. These methods will allow the incorporation of Gene Ontology information into modeling of gene expression data, and facilitate the simultaneous identification of biological processes that are affected by a treatment or another intervention. I propose to incorporate the gene correlation structure into our gene expression model as well as the indicator of the gene group (obtained from the Gene Ontology). The proposed models should allow more realistic fits to real data. We propose to study Bayesian and non-Bayesian alternatives in order to estimate the model parameters. In addition we propose a methodology to help scientists to develop a gene signature (or pattern) that enables the identification of groups of patients related to a condition or disease. This signature is based on a novel gene weighting scheme applied to the standard Random Forest algorithm. I also propose to extend this weighting scheme to other existing classification and prediction methods such as linear discriminant analysis, support vector machines, LASO and others. An additional interesting and important proposed application of these methods is to the analysis of DNA barcodes.

I’m happy to mentor bright and enthusiastic researchers in just about any
area of computer vision, robotics, or perceptual AI. Recent work includes some nascent collaborations with the UR Medical Center, the George Eastman House photographic museum, Kodak research labs, and the Eastman School of Music.

Projects:
1. Energy Replenishment in Sensor Networks
2. WSN-VANET symbiosis for Driving Safety
3. Integrating Isolated Wireless Communication Components for Community Safety
4. Human Sensor Networks

Our team works on a project called BEAM for static analysis of software. It is centered around compiler emulation, data-flow analysis, theorem proving, pointer analysis, inter-procedural analysis. Today the tool is used inside IBM for defect detection.
In the immediate future we would like to push more into parallelization issues, security, specification mining and taking advantage of dynamic analysis.
In the distant future I am also interested in the general issues of software robustness and usability.

I have diverse research interests in intelligent sensor systems. My current research projects are in active perception with microsensor arrays, physiological monitoring with wearable sensors, signal processing for foreign accent conversion, and enhanced face perception with 3D caricatures. Previous research projects include biologically-inspired algorithms for artificial olfaction, audiovisual speech processing, and probabilistic navigation for mobile robotics.

My major interests involve modeling real-world problems as theory problems that can then be analyzed in a formal way. For example, cross-connect designs become graph edge coloring problems, interdomain routing protocols (eg BGP) are seen as game theoretic graph problems, certain optical network scheduling problems are really generalized edge coloring problems (many of which remain open).

In Wireless Networking:

* We are looking at applications and routing services in wireless and mobile networks. We are motivated by the intermittently-connected paradigm and are seeking techniques that unify such models with more traditional well-connected wireless networks as well as wired networks.

In Overlay Networking

* We are interested in network virtualization as the primary technique for deploying connectivity and services in current and future internet technology. Issues of interaction, resource sharing, routing and pricing are of interest.

The current research thrust of our lab is in three different areas (1) Internet Economics: Network Neutrality related issues and Fair Revenue Sharing mechanisms, (2) Wireless Networks: Both mobile as well as fixed infrastructure wireless networks, and (3) Peer-to-Peer Video: Architecture and Cache design for P2P Live Streaming as well as P2P Video on Demand

* Brain Computer Interface

We work with UPMC (University of Pittsburgh Medical Center) to analyze electrical and magnetic signals from human brain. Our goal is to help the patient to re-gain a number of physical activities, even if his/her neuron system is partially damaged. For example, a patient can control a computer just by “thinking”, instead of using a keyboard/mouse. This project involves various aspects of signal processing, machine learning and hardware implementation.

* Improving Circuit Design via Computational Thinking

We apply statistical machine learning to model, analyze and optimize large-scale integrated circuits. Our goal is to maximize circuit performance, improve circuit robustness and reduce manufacturing cost. This project involves various aspects of circuit design, regression modeling, yield prediction and stochastic optimization.

Online Communities

Community Lab project conducts research to understand what leads people to become committed and contribute to online communities and how to design these communities to be more successful.

Social impact of computing

I have been investigating the way people use the Internet in their daily lives and the effects it is having on their psychological well-being and on their social relationships.

Virtual organizations

Groups are inherently different from individuals performing the same task because of a need to coordinate. I have been looking at coordination in groups in both laboratory and field settings and in groups as diverse as research collaborations, managerial teams, military crews at NORAD, projects in Wikipedia and software development teams.

The Center for Policy Informatics (CPI) leverages cutting-edge technology and cross-disciplinary theory to help individuals and communities make and evaluate policy choices. Established in January 2008, the center’s modeling, simulation and theoretical work supports and critiques activities at ASU’s Decision Theater, a world-class interactive 3d immersive visualization environment created to facilitate group decision-making (www.decisiontheater.org ). CPI’s goal is to develop policy-relevant models that balance the complexity of real-world phenomenon with transparent, actionable evidence. Both externally funded and community focused projects provide the center a forum for the exchange of ideas and resources for modeling and simulations.

For example, researchers at the Decision Theater recently developed an interactive table-top event that used both a system’s dynamics model and decisions support system to test coordination strategies between ASU and external agencies during a pandemic outbreak. The participants were leaders in Arizona’s health and education communities. The value of this exercise was immediately relevant when the swine flu broke out and participants referred to their experience with the decision theater as being instrumental in their response.

Future work will be in a number of context including challenges in public health, sustainability, urban growth, crisis management, and related policy decisions. For example, the challenge of discouraging adolescents from smoking must address a multitude of factors that influence an individual’s decision to smoke: peer influence, social networks, physical addictions, environmental factors, family behaviors, genetics, marketing, and individual decision?making. This project seeks to understand the decisions, environments, and pathways in which the major forces of addictive behavior interact. It will achieve this understanding through creation of a systems?based, social?network model for smoking behavior that will spur new scenarios for possible interventions and allow policymakers and pubic?health professionals to visualize the cascading effects of a multitude of individual decisions.

Please refer to the Decision Theater and Center for Policy Informatics websites for a sample of the range and types of research that is possible ( http://cpi.asu.edu/home and www.decisiontheater.org ).

Potential CI fellows will be expected to assist with both current research and to develop an independent research agenda consistent with vision of the Center for Policy Informatics and the Decision Theater at ASU. Fellows with a multidisciplinary background are particularly encouraged to apply.

Our research has two broad thrusts.

(1) Network configuration management: We are interested in exploring radical new ways to simplify enterprise network design and configuration, through the use of task-based and network-wide abstractions. Our research involves bottom-up analysis of network designs through extensive interactions with operators, and systematic top-down algorithms for designing networks. Our research is shedding light on a variety of important and poorly understood domains such as VLANs, reachability, and class of service.

(2) P2P Systems: With the proliferation of P2P systems,it is important to understand their impact on the Internet, and how
they may be deployed in a safe, secure and robust manner.
Our research is exploring issues such as preventing DDoS
reflector attacks exploiting P2P systems, detecting anomalous
traffic patterns of P2P systems, and understanding the impact
of traffic localization policies on ISP networks.

We recognize visual objects with such ease that it is easy to overlook what an impressive computational feat this represents. Any given object in the world can cast an effectively in?nite number of different images onto the retina, depending on its position relative to the viewer, the con?guration of light sources, and the presence of other objects in the visual ?eld. In spite of this extreme variation, biological visual systems are able to effortlessly recognize at least hundreds of thousands of distinct object classes—a feat that no current arti?cial system can come close to achieving.

My laboratory seeks to understand the computational underpinnings of object recognition through a concerted effort on two fronts. First, we endeavor to understand the workings of biological visual systems using a variety of experimental techniques, ranging from microelectrode recordings to visual psychophysics. Second, we attempt to instantiate what we have learned into arti?cial object recognition systems, leveraging recent advances in parallel computing to build systems that begin to approach the scale of natural systems. By combining reverse- and forward-engineering approaches, we hope to accelerate progress in both domains.

I am interested empirical software engineering: the study of software engineering activities in commercial and open-source settings, and the evaluation of processes, models, and tools with respect to outcomes such as cost, quality and interval. I have long record of work in this area, and in several related areas over the last 20 years or so. Please check out my web page, or write to me if you have questions

Current interests focus on analysis and visualization of large collections of photos (e.g., from the Internet). I’m also interested in optical flow, face modeling, and other topics.

We live in a world supported by large-scale IT system and network infrastructures. Many of these systems and networks are mission critical infrastructures and are engineered with tremendous complexity. My research interests focus on the following
topics across multiple disciplines in computer science:
1. Understanding the nature of system complexity by combining data analysis and mining with first principles.
2. Modeling system properties based on system and network knowledge.
3. Developing automated and intelligent solutions based on statistical inference, information theory, optimization, system and control theory.

The current research of the Scalable Computing Software (SCS) group is focused on reducing data access delay and enhancing fault-tolerant computing. Modern High-End Computing (HEC) systems become unprecedented fast in terms of CPU speed and unprecedented large in terms of system ensemble size. However, the technology advance is biased and unbalanced. The fast in CPU speed is worsen the memory-wall problem and the increasing in ensemble size makes fault-tolerant vital of HEC. We have proposed a new I/O architecture for HEC. Unlike traditional I/O, our architecture is based on a novel “Server-Push” model where a data access server, called File Access Server (FAS), proactively “pushes” data in time from a file server to the compute node’s memory. Here the “pushes” includes both “push up” (read) and “push down” (write). This concept is applicable to cache and memory data access as well. In fault tolerance, we combine the merits of both the newly emerged proactive fault tolerant approach and the traditional checkpointing approach to develop the FENCE (Fault awareness ENabled Computing Environment) environment. The SCS group currently has four NSF supported projects, two DoE supported projects, and one industry supported project in the about research areas. These research projects are in collaboration with the Argonne National Laboratory and the Fermi National Accelerator Laboratory, and are partially carried in the two national laboratories. Prof. Xian-He Sun is the director of the SCS laboratory, and a guest faculty of Argonne and Fermi laboratory. More information regarding the SCS laboratory can be found at www.cs.iit.edu/~scs/.

Signal and image processing, pattern recognition, machine translation, natural language processing, source coding, digital libraries, language modeling

Autonomic Computing, Self protection of networks and computers, self control and management of network centric systems, high performance distributed computing, autonomic computing programming, autonomic control and management of networks and applications, autonomic management of power and performance of large scale data centers.

I’m a member of the Media Interaction and Understanding Lab. My focus is mobile systems. How people will use media on these systems and how desktop computing, printing, and other media consumption devices can be used in conjunction with mobile devices. My academic background is in networking, systems, performance and QoS, but for teh past several years my focus is on the use of mobile devices for applications, especially those that involve imaging.

Recently I created and led a project that created a novel mobile consumer application — a mobile media imaging project for a cosmetics consumer application. We solved mobile usability problems, computer vision and color correction, all with any cell phone. Here are some URLs

http://www.sfgate.com/cgi-bin/article.cgi?f=/c/a/2007/07/11/BUG34QU3961.DTL&feed=rss.business

http://www.infoworld.com/archives/videoTemplate.jsp?Id=1330&type=News&tag=Mobile%20Tech

http://www.hpl.hp.com/news/2007/jul-sep/color_match.html

http://www.oprah.com/slideshow/omagazine/2009_omag_beauty_favorites

This application has attracted attention from main stream media and has been licensed to a major cosmetics company. We also built a mobile translation service (text extracted from images) and a home decor color selection application.

Much of my work now is focused on mobile printing, viewing content on the mobile for capture and later use (by printers and other devices). I would love to host someone interested in mobile applications from a usability perspective, applied imaging, mobile web experiences etc. We build demonstrators for the iPhone, Nokia phone, Windows Mobile devices, RIM devices etc. We hope to accept any client device and place much of the computation in “cloud services” designed for specific applications. The ideal candidate should be comfortable prototyping and building systems as well as communicating effectively in written and oral form.

Please feel free to reach out with questions.

Nina