My current research addresses two frontiers in design tools.
For experts, I am investigating how to create the ideal design studio of the future. New input technologies and platforms are rapidly proliferating.
These devices are very promising for professional work because of the richness and nuance of input they provide. I investigate how such technologies can be harnessed to augment professional design practice.

For amateurs, I am developing structured ways of sharing tool expertise and knowledge. Empirical data suggests that designers as well as programmers rely heavily on online resources such as tutorials, examples, and Q&A with online peers to gain expertise. We are working on integrating design tools with online platforms.

Developing and ensuring the reliability and security of software systems by developing innovative software architectures, languages, and tools.

I am interested in Programming Languages and Software Engineering, more specifically, in techniques for building reliable computer systems. My work draws from, combines and contributes to methods the areas of Model Checking, Program Analysis and Automated Deduction. In particular, I have worked on Software Model Checking, the design and implementation of languages and tools for building robust Distributed Systems, and analyses for multithreaded systems software. More recent interests include advanced refinement type systems for statically verifying sophisticated
program invariants (with low programmer overhead) and techniques to analyze information flow and other security properties in modern web applications.

My research typically involves both theory (“proving theorems”) and practice (“building tools”.) In addition to the topics above, I am happy to explore related ideas for potential projects.

Ginkgo BioWorks is a young company out of MIT with the mission of making biology easier to engineer. We engineer organisms to solve challenges across a range of industries from fuels to pharmaceutical production. We aren’t trying to study biology, we are trying to build it – constructing, editing, and redesigning the living world. Our bioengineers make use of an in-house pipeline of synthetic biology technologies to design and build new organisms.

We are looking for a computing postdoc who is passionate about developing CAD tools for the engineering of organisms. You probably have a background in comparative genomics, computational biology, metagenomics, or other similar areas. You have likely been building computational tools to study natural biology — but at Ginkgo you would have the opportunity to apply your skills and tools to the challenge of engineering new organisms.

At Ginkgo, our organism engineers have immediate demands for expanded tools to support organism design. We believe that we provide a unique environment for someone to cut their teeth on real CAD problems in biological engineering. Lastly, we’d be happy to serve as mentors for CIFellows if you are pursuing that fellowship.

The Magnum Group at Virginia Tech is focused on investigating how the powerful processors and variety of sensors in new and planned
smartphones, such as Apple’s iPhone and Android-based smartphones, can be leveraged to build cyber-physical applications that collect sensor
data from the real world and communicate it back to cloud services for
processing and aggregation. The broad dissemination of these
smartphones, their accelerated processing power, range of sensors, and
pervasive cellular connections make them ideal platforms for building these
novel mobile cyber-physical applications. The Magnum Group investigates a broad range of topics in this area, such as augmented reality, crowdsourcing, communications middleware, cloud computing platforms, citizen scientists, traffic accident detection, modeling, and software product-lines. We are continually looking for and open to new ideas in this and related areas.

My laboratory is interested in key challenges in Systems Biology and Medicine. Our larger objective is to decipher biological mechanisms, reconstruct networks, predict phenotypes and build quantitative systems models. Towards this end we continue to develop computational and some experimental methods for integrative analysis of multiple types of biological data and for reconstruction of biochemical networks. It is increasingly become clear that time series data in cellular biology and longitudinal data in mammalian in vivo biology are essential for understanding complex phenotypes and we are developing methods to analyze these data. And most importantly, I subscribe to the view that context-free biology is content-free biology!

My research focuses on programming languages, with applications to software engineering and security. The general goal of my research is to help developers rapidly construct software that is reliable, maintainable, and secure. In the past, I have done research on points-to analysis; type qualifiers; foreign function interfaces; data race detection; network protocol implementations; modularity for C; and ownership systems, among others. Currently, I am working on several research directions, including studying typing scripting languages, working on program synthesis, and studying security on Android.

All of my work involves both theory and practical implementations of software tools.

In addition to the topics above, I would be happy to explore related ideas for projects.

My research is in mobile networking and distributed real-time algorithms based on data mining, with a specific application area in Intelligent Transportation Systems (ITS). Currently in Anchorage, many vehicles are transmitting data gathered from the vehicle’s OBD port back to a central server hosted at the University. This data includes over 200 vehicular parameters. Gathering data from individual vehicles instead of from hardware installed in the roadways at discrete locations allows applications that require much more precise and granular data to be developed. To gather data from individual vehicles requires specialized architectures, such as vehicle-to-infrastructure (V2I) or vehicle-to-vehicle (V2V). The applications that can be developed are endless, with a few examples being fastest paths, traffic congestion improvement, incident identification, roadway slippage determination, and emergency vehicle routing, among others too numerous to include. My research spans the areas of software and network architectures, mobile networking, and distributed real-time algorithms, so an emphasis in any of those areas is acceptable.

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.

My overarching research goal is to use program analysis to ensure software quality of real-world applications, even at industrial scale. My current focus is on the use of tightly coupled static and dynamic program analyses for object-oriented systems. My most recent project focused on performance diagnosis of framework-based systems. We are currently exploring applications of these analyses to problems of security and debugging. We are interested in validating behavioral properties of multi-language applications (e.g., Java and Javascript). There are interesting open research questions about the analysis paradigm being explored such as “In what sense is our dataflow solution ‘safe’?” and “How can we add precision to such analyses?”

The research in our group (PROLANGS@VT) is characterized by problem definition and algorithm design followed by extensive empirical validation. We emphasize finding techniques effective and practical for real applications. Background in program analysis is desirable. Person must be self-motivated and willing to take the initiative in research. Primary responsibility to strengthen research group and help with research supervision of grad students and undergrad students under REU support.

My research aims to improve software dependability through testing, monitoring, and different forms of automated analysis.

My current projects include the development of techniques for transforming existing tests by treating them as data, for lightweight software monitoring, for providing support for end-user programmers, and for adapting program analysis techniques to work in other domains.

Formal Methods / High Performance Computing / Software Engineering / Concurrency

Our main interests are to develop scalable formal analysis methods for high-performance computing systems.
Of particular interest are formal dynamic analysis methods for MPI, shared memory threads, and CUDA/OpenCL, as well as hybrid codes using more than one API. Efficient test generation in these domains as well as coverage enhancing analysis methods are of interest. The Center for Parallel Computing at Utah (http://www.parallel.utah.edu) provides ample opportunities for collaboration including new faculty hire in formal analysis of concurrency.

My interests span programming languages, runtime systems, and operating systems, with a particular focus on systems that transparently improve reliability, security, and performance.

* Reliability and Security

I am interested in systems that transparently improve the reliability and security of deployed systems. Examples of this work include systems that can survive bugs, or even repair themselves by fixing bugs automatically. One of these projects, DieHard, was the direct inspiration for Windows 7′s Fault-Tolerant Heap. Other related projects include Exterminator, Archipelago, and DieHarder. Ongoing work includes systems to protect applications from security attacks with low overhead, and high-performance information flow tracking (“tainting”) to track / prevent information leakage.

* Concurrency

I am interested in systems that improve the performance or correctness of concurrent applications running on multi-CPU / multicore computers. Examples of this work include Hoard, a scalable memory manager that is in use in a number of large commercial settings (e.g., British Telecom, Credit Suisse, Royal Bank of Canada, Cisco…), and Grace, a system that automatically eliminates concurrency errors like race conditions and deadlocks.

The following are my current projects:
1. Formal verification of embedded firmware (NSF funded)
2. Formal foundations of execution models for exascale computing (DARPA funded)
3. Analytics and activity-based intelligence (DARPA funded)
4. New paradigms in machine learning and complex event processing with applications to oil industry and agriculture (funded by BP and the State of Louisiana)

Recently completed projects:
1. Program synthesis and service-based systems (ONR and NRL funded)
2. Reliable middleware (NRL funded)

My current research interests are in incremental analysis and modular analysis for concurrent programs.

In Incremental analysis the differences between closely related program (system) versions serve as the basis for reducing the cost of checking functional correctness and achieving desired coverage of the program. Analyses based on program differences are attractive and have considerable potential benefits since most systems are developed follow an evolutionary process. Functional requirements of a system evolve and change over time. The program sources are changed to match the change in the functional elements. The program is also changed when a fault (bug) is detected and fixed in the program. The challenge with effectively using incremental analysis, however, lies in determining precisely which program execution behaviors are affected by the program changes. We are looking at using data and control flow analysis to conservatively estimate the impact of the change and use symbolic execution to precisely generate program behaviors “affected” by the change.

information integration, query-evaluation algorithms, temporal reasoning,
automata-theoretic algorithms, firmware validation, protocol synthesis, constraint satisfaction, discrete techniques in robotic motion planning

The primary focus of my research is the computer-aided verification and validation of computer systems, including concurrent and distributed systems; security, network and wireless protocols; software systems; biological systems; and safety-critical and embedded systems. Current research projects include the use of Hybrid Automata to Model and Analyze Cardiac-Cell Networks; a Process Algebra for Mobile Ad Hoc Network Protocols; Probabilistic Model Checking of Security Protocols; and Runtime Monitoring of Software Systems with Controllable Overhead.

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

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

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

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

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

I work on projects related to the design and evaluation of large-scale software infrastructure in support of data collection and analytics of social media information during times of crisis and/or mass emergency. My work makes use of techniques and technologies found in software engineering, software architecture, Web application frameworks and REST-based Web services.

Information assurance, cybersecurity, social networking

Software Engineering, in particular, Requirements Engineering, Software Traceability, Software Reliability, Empirical Software Engineering, Software Evolution and Maintenance, Software Architecture and Design, Software Comprehension, Software Project Management, Study of Software Defects.

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

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

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

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

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

Real-time software, specifically: embedded software, cyber-physical systems, models of computation, code generation and optimization, domain-specific languages, architectures for real-time computing, and schedulability analysis.

Several ongoing projects on programming language designs for improving modularity, concurrency, and verifiability that range from language theory to rigorous empirical evaluation of programming language designs to code generation and optimization to program verification. A broad range of expertise is available in our research group in both programming languages/compilers/virtual machines and in software engineering.

We have broad interests in the general area of programming languages and compilers, formal methods, language-based security, program verification, operating system verification, proof assistants, automated theorem proving, and software engineering. Members of our research group are working on building certified OS kernels and compilers, developing new programming languages for writing certified programs, and designing new program logics for reasoning about general safety, liveness, and information flow properties.

My current research focuses on exploring the concept of “behavioral coverage”. The idea is that your favorite verification and validation technique, whether it is testing, static analysis, symbolic execution or some variant or combination of those, produces information about how a program’s behavior conforms, or fails to conform, to expectations. We are interested in developing methods that allow such techniques to “characterize” the portion of a program’s behavior that has been shown to conform to expectations. Moreover, we seek to encode those characterizations in a form that allows the combination of information from a variety of techniques. The resulting combined characterization can be used to target additional V&V or provide developers with a semantic basis for having confidence in system correctness. This project offers an excellent opportunity to collaborate with experts in testing, static analysis, verification, and runtime monitoring and move towards a vision of V&V that breaks out of the silos of individual techniques to provide a holistic characterization of behavioral coverage.

Because of the inherently dynamic personality of next-generation multicore, manycore, and cloud platforms, new techniques to specify, test, exercise, and implement robust software systems on these platforms are required. The central issues here concern scalability and safety: how do we specify, optimize,verify, and implement software systems that adapt seamlessly, efficiently, and safely to changes in the underlying platform? We envision programming models that emphasize concurrency and distribution over localization, and decouple the question of how to structure a highly-parallel or distributed computation from the question of how the resources required to execute it are acquired and managed.

In this context, my research interests explore high-level concurrency and distribution abstractions (including formal semantics, specification, and verification), their implementation (including static and dynamic analysis, and associated runtime support), and low-level abstractions such as weak-memory consistency and associated compilation techniques.

There are many outstanding challenges that must be overcome in this general space. Of these numerous challenges, my research focuses specifically on programming languages, software models, abstractions, and implementation
techniques for these environments. Since an application’s activity may be highly concurrent and possibly distributed, and thus less easily monitored or controlled, new software models comprising programming language design, compiler and runtime implementation, and lower-level architecture-specific protocols are required to ensure robustness, safety, and efficiency.

A central question underlying much of my research is how we can craf robust software systems in the presence of unreliablity, injected from both the underlying architecture and the application itself, without comprising efficiency and scalability.

Thus, effectively dealing with future computing environments requires a symbiotic treatment of software design ranging from language definition and semantics, to software engineering principles related to testing and protocol definition and inference, to compiler and runtime implementation, down to architecture-specific models such as weak-memory consistency. Each of these components contribute
to the realization of a software architecture focused on supporting scalable, robust, and long-lived applications. My research addresses these issues along the dimensions outlined, with specific interests biased towards principled language and system design, and implementation.

My current research focuses on the design and engineering of mobile ubiquitous information systems, from software architecture to application design and user studies. My NSF CPS project “CitiSense – Adaptive Services for Community-Driven Behavioral and Environmental Monitoring to Induce Change” comprises a multi-disciplinary team including software engineering, HCI, embedded systems, AI, security, and medicine. We are designing, implementing, and deploying a mobile sensor system for community-based environmental monitoring. This project will offer excellent collaborative opportunities to a post-doc in software engineering or ubiquitous computing.

My chief research focus is programmer productivity. I develop theoretical and practical techniques and tools for helping people to create, understand, and modify software systems; I perform significant experiments at scale; and I distribute tools to programmers and researchers. My research spans software engineering, programming language design, type theory, static and dynamic program analysis, testing, security, and development environments. My results often stem from cross-fertilization between traditionally separate research areas: experimental vs. theoretical, syntactic vs. semantic, static vs. dynamic, exact vs. inferred, proven vs. statistically likely. Overall, I am to make it easier — and more fun — for programmers to build robust, reliable, secure, and correct software.

I briefly mention several current research thrusts. More details are available at my webpage, http://www.cs.washington.edu/homes/mernst/.

Programming language design and type systems: My research focuses on bringing new capabilities to real languages in a backward-compatible way (which is critical for evaluation and adoption), and building implementations to assess their utility. This pragmatic approach promises to aid both today’s and tomorrow’s programmers, and makes results more likely to have practical impact. The work includes type systems, type inference, and frameworks.

Security: My research addresses three distinct practical problems: measuring unintended disclosure of private data, creating exploits for unknown security vulnerabilities, and fixing bugs that underlie zero-day exploits.

Debugging: Dynamic analysis is complementary to static analysis: although dynamic analysis is often unsound, it can also be more precise, scalable, and applicable to legacy programs. My work applies dynamic analysis, with good effect, to problems that in the past have only been addressed statically, such as type inference and refactoring. It is also useful for reproducing crashes and for reducing false positives in bug-finding tools.

Testing: A common theme in my research is exploiting impoverished test suites. Users seem willing to write small test suites or to supply a few sample executions, but they are reluctant or unable to write more comprehensive or more focused test suites. My research automates these and other testing tasks. The research spans test generation, test selection, test classification, and test execution.

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 am currently working on another highly-scalable distributed system that can make certain aspects of Web programs much more efficient and easier to program.

The computational aspects of the research include signal analysis, modeling and optimization of procedures, improved methods of modeling to provide robust conclusions from experimental data.
The lab’s experimental research interests focus on the structural biology of protein domains in intracellular signal transduction, including SH2, SH3, kinase, phosphatase, PH domains, and many others and how natural ligands interact with them. An additional area of interest is the development of NMR and related methods for structural biology. Projects include segmental labeling, other novel isotopic labeling methods, and detection of protein-protein interaction surfaces and dynamics.

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

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

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

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

More and more computer systems are built as integral parts of many of today’s systems and devices to monitor and control their functions and operations. These embedded/networked systems often operate in environments where safety is a major concern. These computer systems must be highly dependable and timely. My teaching and research focus on building these real-time, embedded systems, and cyber-physical systems. Research topics include: scheduling, formal verification, networking, power-aware techniques, real-time security, and software engineering.

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

Safety-critical, dependable &/or reliable software systems and product lines, evolving requirements, defect analysis, monitoring and diagnostics, compositional verification, automated requirements engineering

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

I am broadly interested in formal, automated methods for program verification and synthesis, in particular abstract interpretation and model checking. I am also broadly interested in languages, models, and systems for parallel programming.

I am seeking a postdoctoral researcher to work with me on Cauchy, a long-term project aiming to build an “analytical calculus of computation”: a system of mechanized reasoning that can verify whether a program satisfies “analytic” properties like continuity and smoothness, and compute derivatives, discontinuities, limits, and other analytic attributes of programs. The practical motivation of the project is to develop a new class of program analyses for an era where computing is intertwined with sensor-derived perceptions of the physical world, and correctness is a continuum rather than a boolean fact. For example, we may now require that the program be “robust” to small amounts of uncertainty in its inputs—i.e., that small perturbations to an input state only lead to small changes to the output state. A way to formalize this statement would be to define a metric space over the states of the program, and ask that the program encode a continuous function over this space. Alternately, we may consider the Lipschitz constant of the program as a measure of its robustness. To tune program parameters, we may want to use classical root-finding techniques, which may only work on an analytic approximation of the program. To argue that a program converges, we may want to compute limits on its outputs as time elapses to infinity. Common to the above scenarios is the need for some form of analytic reasoning about programs.

The scope of Cauchy includes the theoretical foundations of such reasoning, ways to automate it using state-of-the-art constraint-solvers and numerical optimizers, and its applications in program verification, synthesis, optimization, and approximation. From evidence so far, Cauchy opens a new playground for research on reasoning about programs. It also raises the possibility of a fruitful union of program semantics and verification with control theory, numerical analysis, machine learning, and computer algebra.

My main research focus is on Software and Systems Security. It is driven by practical problems, and emphasizes building real systems. It draws on principles and techniques from programming languages and compilers, algorithms and operating systems to address problems such as:

* Binary analysis and instrumentation for security applications
* Principled and proactive defenses against malware and untrusted code
* Source-code analysis/transformation to mitigate software vulnerabilities (memory errors, SQL injection, XSS, …)
* Attack isolation and recovery; Self-healing systems
* High-performance intrusion detection (network and host-based)

Please visit Secure Systems Laboratory (http://seclab.cs.sunysb.edu/) for a detailed description.

Develop natural language processing (computational linguistic) methods for analyzing clinical free-text, emphasis on neuro-psychiatric text.

My research interests center on tools and techniques for building, understanding, and ensuring reliable computational systems. Much of my work centers on finding novel ways of interacting with the programmer to design more precise and practical program analyses to produce more effective programming systems.

The Xisa project is an instance of this approach that infers precise properties of complex data structure manipulations. The novelty of Xisa is that it extracts both the necessary invariants and reasoning rules from executable assertions. This approach allows the developer to focus the analysis to the properties of interest and without using a separate formalism for testing and static analysis.

Another project called Mix looks at an incremental combination of analyses with different precision, such as type checking with symbolic execution. The observation is that with user interaction, an analysis need not prove all the desired properties at once.

Have you ever felt a compiler/analysis tool misunderstood what you meant in your program? The Gradual Programming project examines this disconnect between the intent of a software developer and the meaning of the program according to the language semantics. In the end, we envision a programming system where the developer and tools interact to agree upon the precise meaning of a program.

My research interests are in two areas: Architectures and algorithms for effecient collaboration between mobile devices and sensor networks, especially for the purpose of sampling sensor-field data; and modeling and analysis of concurrent/distributed software systems.

My interests are in model checking programs, probabilistic systems, and hybrid systems. I am also interested in the core areas of logic and automata theory.

I have two main projects going on: (1) Sourcerer, and infrastructure for collecting, indexing and analyzing large amounts of open source code with the goals of gaining empirical insights into how people write programs and developing innovative software engineering tools that leverage this large amount of existing code; (2) OpenSim, an open source platform for massive multiuser online virtual environments designed to be the next generation 3D web. I am interested in mentoring CI Fellows for work of mutual interest in any of these projects. The first is at the border of information retrieval and software engineering; the second is primarily middleware for interoperability in the 3D web.

The goal of my research is to find ways to help programmers create correct, reliable, and secure software. To address these issues, I work on methods to manipulate programs and analyze their properties. Often these have taken the form of frameworks that apply to general classes of problems.

Much of my current focus is on methods to analyze machine code (a.k.a. “binaries” or “stripped executables”), but I am also interested in other challenging program-analysis problems, such as analysis of concurrent programs and programs that use linked data structures.

My research interests are in the application of formal methods to system-level design. Specifically, development of semantics and language-based techniques for representing, synthesizing and verifying complex, heterogeneous systems. Of specific interest is investigating system-level impacts of security requirements on high-assurance systems, and techniques for synthesizing such systems from specifications. My current applications include defining a coalgebraic semantics for the Rosetta specification language and using Rosetta to specify, synthesize and verify elements of high-assurance operating systems, software defined radios, and smart grid components.

Static analysis of complex software systems, with the goal of optimizing, securing and parallelizing such systems.

Right now, my group is working on a range of projects, including accelerating classical static analysis with GPUs, automatic parallelization of functional programs, deep shape analysis of object-oriented programs and software understanding tools for legacy code.

We’re also making foundational thrusts aimed at improving the speed and precision of static analyzers in general.

I’d be happy to mentor CIFellows with interests in or a near any of these topics. Please contact if interested!

My current research interests focus on applying software engineering methods, techniques, and models to the design and development of intelligent, complex, adaptive, and autonomous multiagent systems. My research in this area is currently focused on building the tools and techniques necessary to design and build cooperative robotic systems, where the robots work autonomously, but cooperate as part of a team. I am also interested in building and developing hybrid intelligent systems that include humans, software agents, and mobile hardware agents.

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

The mobile and pervasive computing group at the University of Texas at Austin focuses on challenges related to the support for and use of opportunistic networks. Opportunities include work on an autonomous robotic testbed; abstraction and middleware development for pervasive computing, delay tolerant networks, and sensor networks; usability issues for mobile and pervasive computing; and understanding and presenting the uncertainty of operating in opportunistic networks. For more information and recent publications, see http://mpc.ece.utexas.edu.

I seek a post doc to work with me on projects dealing with coordination in distributed software development. More specifically, projects in my group include data collection and analysis of large-scale software systems, and system design and development to implement cutting edge coordination tools (e.g., Palantír – an eclipse plugin that tracks changes and predicts conflicts, Tesseract – a browser based application that enables interactive exploration of different project entities). My work is placed within the broader context of the Software Engineering lab at UNL (Esquared lab). We have very strong connections with industry, fueling the projects we work on and providing us with interesting opportunities for testbeds.
Within the broad interests, there is room for you to pursue your own projects, though I would also expect you to join in working on grant proposals, papers, advising, etc.

My current research interests are in two broad areas: the automatic analysis of software (either static or dynamic) for verification or bug finding, and in programming highly parallel machines, in particular programming heterogeneous machines with complex memory hierarchies.

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

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

I’m a glaciologist who studies various parts of ice sheets with numerical models. These models require solutions of various PDEs on various platforms. One of my interests is a development of large-scale ice-sheet model as a part of a Global Climate Mode.

http://www.princeton.edu/aos/people/research_staff/sergienko/index.xml

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

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.

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.

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.

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

Please see my home page and publications.

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:

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 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

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.

Over the last few years, I’ve authored over seventy technical papers on the subjects of software engineering and network reliability. I’m currently leading Avaya PolyFlow research project to produce a product line of flow analysis tools. The project aims to improve software quality with reduced cost by removing defects at earlier stages of software development. Our technologies include effective network/program structure recovery, instrumentation for monitoring, code coverage criteria selection, flow analysis, flow slicing and automatic test generation.

PROJECT 1 is developing tooling and analysis techniques to enable
performance optimization in support of large commercial workloads in
the massive multicore era in which systems have hundreds or thousands
of processor cores. PROJECT 1 involves working with large-scale,
commercial applications with an eye towards dramatic improvements in
the performance of critical enterprise software deployments. This
project would benefit from postdocs whose research focuses on such
issues and who have experience with deployment and performance
analysis of multi-tier web applications, and more particularly
experience with Java programming, scripting (Javascript, Awk, Perl),
Java EE, database setup and tuning.

PROJECT 2 also focuses on future system architectures with large
numbers of multicore processors, but with a particular focus on how
such systems incorporate solid state disk / memory. PROJECT 2 is
analyzing how software can best take advantage of SSD and multicore
advances and what algorithms and architectures are best suited to
these systems — with approaches again focused on critical enterprise
workloads. This project would benefit from postdocs whose research
focuses on such issues and who have experience in storage systems and
disk modeling and with good knowledge of system benchmarking,
performance modelling, flash memory design, and interfaces such as
Sata and PCIe.

I’m broadly interested in formal methods for building scalable and adaptive distributed systems. I have a particular interest in scheduling and resource allocation and in the application of control theory to construct solutions. Part of the application of control theory is a blending with software engineering so that practitioners can exploit these techniques.

broadly interested in programming languages, software engineering, and computer security, with a particular focus on techniques and tools for improving software reliability & security, and programmer productivity.

Static timing analysis and statistical timing analysis of VLSI circuits, process variation analysis, at speed structural testing of digital circuits, circuit analysis, signal integrity, optimization of digital circuits, coupling noise analysis in digital circuits.

The FASTlab (Fundamental Algorithmic and Statistical Tools Laboratory), consisting of 19 people including 11 PhD students, works on the problem of how to perform machine learning/data mining/statistics on massive datasets, and related problems in scientific computing and applied mathematics. We employ a multi-disciplinary array of techniques from machine learning, nonparametric statistics, convex optimization, linear algebra, discrete algorithms and data structures, computational geometry, computational physics, Monte Carlo methods, distributed/cloud computing, data visualization, programming language theory, and automated theorem proving. We have developed the current fastest algorithms for several of the most fundamental machine learning methods. We also develop new machine learning methods for difficult aspects of real-world data. Our work has enabled high-profile scientific results which have been featured in Science and Nature. We strive for first-of-a-kind analyses of massive datasets from domains such as cosmology, cancer diagnosis, spam blacklisting, and retail transactions.

Our main interests are in the formal specification, verification, and certification of software-based systems using static and dynamic analysis, model checking, and deductive methods. Our group has developed verification and reasoning systems such as PVS, SAL, Yices, and PCE (Probabilistic Consistency Engine). We have applied these systems to a number of sequential and distributed algorithms. We are also active participants in the Verified Software Initiative and the related VSTTE conference.

See my home page: www.cis.upenn.edu/~lee

The Critical Systems Research Group (CriSys) at theUniversity of Minnesota is conducting research in software engineering and is investigating methods and tools to help us develop software with predictable behavior free from defects.

Research in this area spans all aspects of system development ranging from concept formation and requirements specification, through design and implementation, to testing and maintenance. In particular, we are currently investigating model-based software development for critical systems.

Specifically, we are focusing on how to use various static verification techniques to assure that software requirements models possess desirable properties, how to correctly generate production code from software requirements models, how to validate models, and how to effectively use the models in the testing process.

Dr. Ole J. Mengshoel is a Senior System Scientist with CMU Silicon Valley at the NASA Ames Research Center. His current research focuses on reasoning, diagnosis, decision support, reasoning, and machine learning under uncertainty – often using Bayesian networks – with aerospace applications of interest to NASA. Additional research interests include resource allocation and scheduling in real-time systems, intelligent user interfaces, information assurance, evolutionary algorithms, knowledge acquisition, and knowledge engineering. Dr. Mengshoel has managed and provided hands-on leadership in a wide range of research and development projects. He has successfully developed technical results and software that have or are being matured and transitioned into the aerospace, defense, finance, education, electronic commerce, and manufacturing sectors. Dr. Mengshoel has published over 35 articles and papers in journals and conferences, and holds 4 U.S. patents. He holds a Ph.D. in Computer Science from the University of Illinois, Urbana-Champaign. His undergraduate degree is in Computer Science from the Norwegian Institute of Technology, Norway (now NTNU). Prior to his work with NASA, he was a research scientist in the Knowledge-Based Systems at SINTEF (Scandinavia’s largest independent research organization) and in Decision Sciences Group at Rockwell Scientific.

The research group I am leading has been active in wireless sensor networks for a number of years. We have created the first WSN-based countersniper system, the FTSP time synchonization protocol, radio interferometric positioning and Quasi Doppler localization, among others. We are quite active in the TinyOS community. Our current projects include environmental monitoring, structural monitoring, acoustic tracking, radio localization and others. We are looking for bright people to participate in our research.

My research interest has always been human-computer collaboration, in particular how to assist people in performing complex, knowledge-rich tasks that cannot be fully delegated to a computer program. This raises many research questions: How can people provide a computer with enough knowledge about the task domain and the user’s context to provide adequate assistance? How could we make it easier to provide the knowledge needed? How do we know that the computer understands the knowledge that it is given and can make effective use of it? How can a computer be proactive in asking questions about what it does not know and is needed to improve its behavior? All these questions span a number of research areas including knowledge acquisition (or knowledge capture), intelligent user interfaces, knowledge representation and reasoning, problem solving and decision making, and lie in the intersection of artificial intelligence, cognitive science, and human-computer interaction.

Many of my current projects focus on the knowledge-rich task of scientific data analyses that lead to discoveries. We cast complex analyses as computational workflows, which represent complex compositions of software components and the dataflow among them. Workflow systems can then support scientists by automating low-level aspects of the process, providing detailed records of each analysis and its products, and enabling rapid reuse of software compositions.

Other recent projects focus on information trust, knowledge collection from web volunteers, and learning complex procedures from human tutors.

In the area of software engineering, we have been working on techniques for detecting faults in software systems. We have been developing the FLAVERS finite-state verification system, which uses data-flow analysis techniques, to determine whether a system adheres to user-specified properties. Versions of FLAVERS currently exist for Java and Little-JIL, a process modeling language. To help analysts specify properties, our team is developing PROPEL, a property elicitation systems, that provides templates for commonly occurring property patterns. Analysts can complete the templates using natural-language phrases, decision trees, or finite-state automata representations, or some combination of these three. In the area of software architecture, we are developing an approach for defining component interactions that supports evolution and simplifies reverification, leading to a better platform for plug-and-play component-based development.

Recently we have been applying these technologies to processes such as medical procedures or election processes. In the medical informatics area, we are defining critical medical processes in the Little-JIL process definition language, and then using FLAVERS, PROPEL, and an assortment of safety analysis techniques to detect possible errors or vulnerabilities. In the digital government area, we are evaluating approaches for improving trustworthiness. We have been looking at techniques to help make election processes more secure and working with the National Mediation Board on how to make negotiation processes more transparent and trustworthy.

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.

My research interests focus on ways to create easier to use software tools.

To understand how to make software tools easier to use, I conduct studies of programmers and end-users using existing software tools and create cognitive models of tool use. I also work with people who are designing and developing new software tools to help them create tools which are easy to use.

I am also interested in providing tools and methodologies that allow designers who do not have a background in psychology of programming to use psychological theories to guide their design choices.

Jaakko Järvi is an assistant professor in the department of Computer Science and Engineering, and belongs to the Parasol lab (parasol.cs.tamu.edu). His current research interests includes a generic and declarative approach for programming user interfaces, with a goal of obsoleting most of the event handling code that is necessary and abundant in todays GUI frameworks. Besides user interfaces, he investigates how the approach extends to software construction in general.

My research is focused on parallel C++ libraries, optimizing compilers for parallel computing
including automatic parallelization and parallel applications (like particle transport, hydrodynamics and other DOE funded applications).
I am also interested in novel parallel architectures, and the general use of speculation for parallel computing.

The Parasol Lab is interested in C++ compilers, generic programming, computer algebra,
motion planning, protein folding, computational geometry, distributed computing, ….see more
at parasol.tamu.edu

My research interests are in the field of software engineering. The underlying theme, and long-term goal, of my research is to devise techniques and tools that aid with the construction, analysis, and maintenance of large-scale distributed and embedded software systems. The inherent complexity of large-scale software systems has always posed a significant challenge to software practitioners. On top of this, an emerging class of non-conventional computing domains (e.g., embedded, pervasive, and mobile) are presenting the practitioners with a formidable set of new challenges: heterogeneity of both hardware and software, limited computing resources, mobility, scalability to large amounts of data and numbers of devices, dynamic reconfigurability, rapid composability, and so on.

The overarching hypothesis of my research is that an architectural focus can also remedy many of the difficulties posed by the newly emerging class of non-conventional computing domains. My work to date has investigated a wide range of issues in the area of distributed and embedded software architectures: self-* systems, architectural middleware, modeling and estimation of Quality of Service (QoS) properties, software deployment, and architectural analysis.

We are exploring collaborative work among geographically distributed team members, both in areas of science and engineering, and virtual teams in companies. We conduct both laboratory and field studies, and have also been doing some agent-based modeling of virtual teams.

Real-world use of multi-core systems requires the development of distributed programming methods for inter-core communication. This fact is evidenced by the formation of the Multi-core association (MCA) and the development of the Multi-core Communications API (MCAPI, http://www.multicore-association.org) supported by more than 20 industrial member companies. MCAPI targets the transport layers within future multi-core SOC systems and is hoped to become the industry standard. Like the message passing interface (MPI) API for cluster computers, MCAPI is inherently complex leaving it vulnerable to ambiguity in specification, implementation, and slow adoption. To address these concerns, ensure the absence of nasty bugs, and guarantee conformance to product specifications and user expectations, we propose to employ formal specifications to characterize MCAPI; formal analysis methods to ensure that MCAPI applications are bug-free and conform to specifications; and field validation of our ideas with the help of Industrial Mentors who have expressed willingness to provide us driving examples, monitor our progress, and give feedback. The work explores technologies to improve design quality in complex APIs, facilitate multiprocessor programmability in future SOC products, and provide design verification in both hardware and software layers. In the first year we shall acquire a thorough understanding of MCAPI and other APIs such as MRAPI for resource interactions. With this understanding, we will develop a formal specification for MCAPI that can help answer putative (“what if”) queries about various scenarios of using the API. Since the uniqueness of MCAPI lies in its use of light-weight message passing in addition to shared memory consistency, understanding the formal semantics of MCAPI is crucially important. We expect this specification to help us garner valuable high level properties about MCAPI that can serve as incisive default correctness properties to verify on application codes that use MCAPI. In conjunction with the development of the formal specification, we will work on a verified golden execution model that can be used by developers to begin testing programs. The golden execution model will also serve as a reference solution for other implementations. The second year of the project is to develop dynamic execution methods that can efficiently verify MCAPI application codes directly (without model building) and also significantly reduce the number of program schedules to be examined using new partial order reduction methods. The dynamic verification engine will critically rely on the golden execution model for a runtime environment, and the partial order reduction will critically rely on the formal MCAPI specification to understand dependency relations in the API. The work in the third year of the project will be to enhance a user given test harnesses for MCAPI applications through symbolic methods thus removing the need for a closed test environment. A significant challenge to overcome in doing this generalization is how to propagate information across the API calls.

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

I have worked in many areas of software engineering from the most theoretical to the most applied and everywhere in between. My primary interests focus on software quality. For the last 7 or 8 years my group has been developing statistical models that accurately predict the location of defects in the next release of a large software system. We have done several empirical studies using large 24/7 industrial systems to evaluate the effectiveness of our algorithms. I have also developed a number of well-known software testing approaches, and have done research in software performance testing.

Interests from web site:
* Language mechanisms for abstraction (program generators, DSLs, modules and components, extensible languages, meta-programming, multi-paradigm programming)
* Languages and tools for systems (programming models for concurrency, language support for distributed computing, memory management and program locality)
* Program analysis and testing (automatic test generation, invariant inference, symbolic execution, pointer analysis).

See URL for more.

My main research focus is on developing compiler algorithms, runtime systems, and tools that enable programmers to use a high-level programming style and modern languages, and yet still achieve high performance on modern architectures. I am particularly interested in effectively using processor memory hierarchies, and in memory management.

I am very interested in future architectures and their compilers that are a better match to current and future technology limits and constraints. Explicit Dataflow Graph Execution (EDGE) is the approach we are pursuing.

See my publications page for a sample of our recent results:

http://www.cs.utexas.edu/users/mckinley/papers.html

Performance and Dependability Analysis of Computer Systems.
Architecture-based Software Reliability
Analysis of Web-based Systems
Understanding and Modeling Web Robot Behavior

safety-critical and dependable product lines, software evolution, compositional verification, automated requirements engineering.

digital libraries, information retrieval and visualization, multimedia, software engineering, hypertext, computers and education

The goal of my research is to create systematic methodologies and conceptual tools to design interactive applications which are not only usable, but also effective communication artefacts for all the stakeholders involved.

To this end, the specific scope of my research encompasses the modelling of the user experience for hypermedia and content-intensive web applications, from requirements analysis, to design and usability evaluation, with the purpose of supporting organizations and institutions to better communicate with their audience through new media, and contributing to a better understanding of technology-enhanced communication.
The topics of investigation include:

user experience modelling and design
design methodologies for content-intensive web applications, hypertexts and hypermedia
information architecture design methods and principles
interaction between requirements, design and usability
requirements analysis, knowledge elicitation and communication in technology-based projects
usability and accessibility evaluation methods

Research results are methodological and practical advances to the analysis, design and evaluation of interactive applications in various domains, including Cultural-Heritage, Health communication, eLearning, eGovernment and Bioinformatics.

Design, specification and verification of concurrent software systems. Specification-based testing and concurrency analysis. Leveraging synchronization contracts for D4V (design for verification).

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).

My research interests lie in the areas of Information and Systems Security, Policy Analysis, and Health Care Privacy. We have developed algorithms for analyzing Administrative Role-Based Access Control Policies and developed access control mechanisms for securing scientific workflow provenance. My research in the area of systems security focuses on operating systems security and the use of virtual machine to provide security. My research in the area of privacy focuses on addressing the privacy issues in health care systems and developing techniques for formal analysis of privacy policies.

My primary research interests are in modeling and testing software developed using the object-oriented, aspect-oriented, and component-based paradigms.

In the area of modeling software systems, we have developed techniques for aspect-oriented modeling, model composition, model transformation (including transforming UML models to Alloy), and animating and testing UML models. We have developed and implemented a technique for composing UML class models. We have developed a model-driven approach for incorporating extra-functional concerns in middleware-based applications.

In the area of software testing, we have developed and evaluated mutation analysis approaches for component-based and aspect-oriented programs. We implemented a bytecode fault injection tool for Java. We have developed and implemented an aproach that produces test inputs from UML design models. We are currently working on dataflow analysis of object-oriented and aspect-oriented programs.

We have worked on refactoring large legacy systems using aspects and evaluated the costs and benefits of using aspects over several revisions of the software. The benefits were measured in terms of enhanced maintainability.

We are collaborating with a team from the infectious diseases research group at Colorado State University to develop an adaptive disease surveillance, prevention, and control information system for vector-borne diseases.

My primary research focus is on rigorous modeling of complex software systems. The research I am engaged in spans the use of models at development time (requirements, architecture and detailed design models) and at run-time (models used to support run-time monitoring and adaptation of software).

In the development area, our research focuses on providing support for rigorous analysis of UML models (e.g., transforming UML models to Alloy models; transforming UML models to performance estimation models), model transformations, animating and testing design models, and for synthesizing designs by composing models describing different system aspects. The latter research area (design synthesis) is a major research focus. The particular synthesis approach we are developing is called Aspect-Oriented Modeling (AOM). In AOM , a design consists of models describing different aspects of a systems (e.g., security, fault tolerance, safety, and core functional aspects). An integrated view of the design is synthesized by composing the models. We are developing model composition techniques that are capable of uncovering undesirable emergent properties that arise as a result of interactions across the different system aspects (e.g., fault tolerance features may work against the goals behind security features).

In the software adaptation area, our research is focused on the use of development models at run-time to support dynamic adaptation of software. We are currently working with a team from the infectious disease research group at Colorado State University to develop an adaptive disease surveillance, prevention, and control information system for mosquito-borne diseases (e.g., dengue fever and malaria).

We are trying to build more effective mobile robots by trying to emulate systems from cognitive science and neuroscience. We are developing algorithms for large-scale spiking neural networks, with Hebbian learning, for serial or parallel computers. We are also implementing cognitive architectures on mobile robots.