The Ken Kennedy Institute brings together the Rice community to foster innovations in computing and data science. Check out the list below to learn about how Rice University faculty are applying data and computation to Analytics in Business, Humanities & Social Sciences.

• Professor Zoran Budimlić is currently leading CnC-Madness, a multi-institutional NSF research project, whose goal is to develop new programming technologies based on CnC, a declarative, data-flow model for expressing and executing irregular tree-based scientific applications.  
• Professor Robert "Corky'' Cartwright has devoted his career to elevating programming from a black art to a systematic discipline. To this end, he has: conducted fundamental research on the mathematical principles governing the design and implementation of programming languages, helped found an outstanding academic Computer Science department at Rice University, and served as a professional leader in programming language research and computer science education. His current research focuses on developing extensions and programming environments for existing languages as well as developing new programming languages.
• Professor Keith Cooper’s primary research area has been program analysis and optimization.  He was one of the founding members of the compiler group at Rice and continues as an active researcher and mentor. He has a history of work in algorithm development, procedure optimization, register allocation, and instruction scheduling. His current research interests include processor-model dependent optimization, either ahead of time or at runtime, and efficient, automatic discovery of critical performance parameters of processors and systems.
• Professor Kostas Mamouras is currently working on the design of programming abstractions for processing data streams. Several real-time decision-making applications rely on the computation of quantitative summaries of very large streams of data. His team have proposed StreamQRE, a declarative query language that combines regular expressions, quantitative aggregation, and relational features. A compilation algorithm translates the high-level query into a streaming algorithm with precise guarantees for resource usage. He is also interested in program semantics and logics for program verification. In particular, this includes equational theories of programs based on the framework of Kleene Algebra with Tests.
• Professor John Mellor-Crummey's research focuses on software technology for high performance parallel computing. His current research includes tools for measurement and analysis of application performance, tools for dynamic data race detection, and techniques for network performance analysis and optimization. He leads the research and development of the HPCToolkit Performance Tools, principally supported by the Exascale Computing Project. His past work has included development of data parallel compilers, runtime systems for scalable parallel computing, scalable software synchronization algorithms for shared-memory multiprocessors, and techniques for execution replay of parallel programs.
• Professor Krishna Palem’s research interests are focused on all aspects of embedded computing, include adaptive architectures and computing, algorithms, compiler optimizations, embedded systems, low energy computing and nanoelectronics. He is the founding director of VISEN center at Rice University. His current research areas include Adaptive and reconfigurable computing, Algorithms, Applied Probability, Compiler optimizations, Embedded systems, Low energy computing, Nano-scale Electronics and Computing, and Technology for societal benefits.
• Professor Moshe Vardi is a member of the American Academy of Arts and Sciences, the National Academy of Sciences and The National Academy of Engineering. His research interests focus on automated reasoning, a branch of Artificial Intelligence with broad applications to computer science, including machine learning, database theory, computational-complexity theory, knowledge in multi-agent systems, computer-aided verification, and teaching logic across the curriculum. He is the author and co-author of over 600 papers, as well as two books: Reasoning about Knowledge and Finite Model Theory and Its Applications. He is also a Faculty Scholar at the Baker Institute for Public Policy at Rice University. Alongside scientific research, he also investigates issues in science and technology policy, such as AI ethics.
• Professor Beatrice Reviere has worked extensively of the development and analysis of numerical methods applied to problems in porous media and in fluid mechanics. Her current research deals with the development of high-order methods in time and in space for multiphase multicomponent flows (in rigid and deformable media); the modeling of pore scale flows for immiscible and miscible components; the numerical model of oxygen transport in a network of blood vessels; the analysis of neural networks for image segmentation and the design of iterative solvers.
• Professor Jesse Chan’s research interests are in numerical methods for PDEs and scientific computing. More specifically, his recent work has focused on high order finite element and discontinuous Galerkin (DG) methods, provably stable methods for wave propagation and fluid dynamics, efficient high performance implementations on many-core and GPU architectures, and discontinuous Petrov-Galerkin (DPG) methods. His research works are central to scientific fields from environmental and aerospace engineering to solar physics.