New Faculty

shelat's research focuses on the modern study of cryptography. He investigates techniques for facilitating interactions between distrustful entities (e.g., automated tellers, wireless networks, internet banking, satellite radio/TV, etc). He emphasizes rigorous methods in combination with precise yet practical definitions and assumptions. Recent works considers topics such as exploiting imperfect reference strings, efficient access to untrusted shared memory, adaptive oblivious transfer, obfuscation, non-interactive and fair zero-knowledge proofs, collusion-free protocols, digital fingerprinting, and data compression.

Sherriff's research interests are in empirical software engineering and computer science education. His recent work has focused on using singular value decomposition with software development artifacts to highlight relationships within software systems. These relationships are based upon empirical records of system development and maintenance and can describe the evolution of the software system. When these relationships are coupled with verification and validation techniques such as static analysis or regression testing, maintenance and testing efforts can be directed based upon historical evidence of where previous faults have occurred. He also developed the Defect Estimation with Verification and Validation (V&V) Certificates on Programming (DevCOP) system for creating a persistent record of V&V practices as certificates, which can then be referenced later during the development and maintenance of the system.

For more information about Prof. Whitehouse's research, please visit his personal home page.

Lawrence's research explores techniques for integrating empirical data into the computer graphics pipeline. The goal of his work is to enable artists, designers and hobbyists to easily acquire and incorporate measurements of complex real-world phenomena into synthetic imagery. Reaching this goal will require addressing open research problems related to the efficient acquisition, representation, storage and retrieval of high-dimensional datasets commonly encountered in graphics. He introduced several new representations for surface reflectance functions derived from measured data. He is investigating generative probabilistic models for representing a broader class of light transport functions.

Weimer's main research interest focus on advancing software quality by using both static and dynamic programming language approaches. Software quality and reliability are increasingly important, but software remains buggy. Weimer is particularly concerned with automatic or minimally-guided techniques that can scale and be applied easily to large, existing programs. He believes that only finding bugs is insufficient, and so he investigates ways to help programmers address defects and understand error reports. He is also interested in designing languages and features to help prevent errors. He uses concepts from other areas of computer science to help address software quality problems, and his research combines elements of databases, systems, and machine learning. One of his projects involves adding programming language support for more robust error-handling via first-class compensation stacks. It also uses specification mining techniques to automatically infer important resources and safety policies in the presence of run-time errors.

Gurumurthi works in the area of computer architecture. His research group is currently exploring issues related to data center energy management, silicon reliability, and memory systems and I/O. Gurumurthi's research contributions include complete-machine power simulation, dynamic RPM (DRPM) disk drives, intra-disk parallelism, temperature modeling and management of storage systems, techniques to improve the performance of redundant multi-threading, and runtime architectural vulnerabilty estimation techniques. His research is funded by the National Science Foundation, Intel, Google, and Hewlett-Packard.

Hazelwood's research interests include all aspects of optimizing compilers and computer architecture. She focuses on infrastructures for and applications of dynamic binary modification. Her earlier work investigated the problem of caching and managing modified code. She has also explored several program optimizations that can be applied at run time. More recently, she has been interested in applying dynamic binary optimizers to the areas of low-power computing, reliability, and embedded systems. She collaborates on the Pin Project and leads the Tortola Project.

Bloomfield's research interests in computer graphics and user interfaces focus on haptics: using the sense of touch to provide feedback to a virtual reality user. For example, by placing small, vibrating motors (aka 'tactors') on the skin's surface, the user can 'feel' the virtual world as they move through it - the tactors activate when the user collides with an object in the virtual environment. He is also interested in computer science education, specifically the undergraduate experience.

Soffa's research interests include  virtual execution enviornments, binary level optimization, path sensitive program analysis, and software tools for debugging and testing programs. One research project  deals with  developing an advanced execution system, called a Robust Execution Environment (REEact), that will dynamically adapt an application’s execution to the runtime resource landscape originating from runtime variations.  This research project  In another project, she,  with a Ph.D. student Wei Le is developing a path sensitive query based system for program analysis that is useful for detecting various types of software vulnerabilities.  She is also working on parallelizing software to exploit a multi core architecture.