The Center for Science of Information brings together researchers from diverse fields to develop models and methods for diverse applications. Partner universities include:
Faculty members, who have expertise in computer science, computer engineering, and the use of personal robots in education, will enhance existing courses such as emergence, visualizing information, and computational modeling based on SOI. They also will develop texts, modules, and training materials for an undergraduate SOI course. The university also will host the center's full-time director of diversity (funded in partnership with Howard University) to broaden the pipeline of students pursuing advanced degrees and careers in the science of information.
Howard University boasts strengths in computer science education, technology transfer, information security, algorithms, and distributed computing, particularly in the application of distributed high performance computing to solve computational science problems in biology, physics, and chemistry. Along with creating a course in computational biology and strengthening the science of algorithms, Howard researchers will help SOI team members create a model for attracting and retaining a diverse range of students into the STEM (science, technology, engineering, and mathematics) pipeline.
MIT researchers specialize in the physical and computational aspects of information, two key components in the development of information theory. From a physical aspect, the researchers will help SOI team members apply quantum physics principles to modeling physical behavior and manipulating information in physically feasible ways. Similarly, by discerning computational abilities and limits, they will assist the team in setting targets for exploring information behind various processes.
Researchers at Princeton possess expertise in communication networks, wireless communications, information theory, wireless multimedia, signal and image processing, multiresolution signal analysis,video coding, and adaptive and learning systems. Focusing on theoretical work, they incorporate the use of computers for system simulation and optimization. Their expertise will help the SOI team expand traditional information theory to such fields as economics and biological networks, reexamining them in applications with severe delay constraints.
Purdue is the lead institution for SOI, providing expercomputer science, statistics, psychology, chemistry, biology, and engineering. The university has an extensive infrastructure for seeding and managing large, multi-institutional efforts through Discovery Park, an interdisciplinary facility on the West Lafayette campus that addresses global grand challenges. Purdue also is home to the largest academic Condor flock in the world, comprising more than 14,000 computers.
Long a hotbed of research in network information theory and wireless technology, Stanford has made significant contributions to these fields, from faculty development of commercial applications to alumni leadership roles in related technology companies. Today, Stanford researchers are focused on developing connections and interplays between information, communication, estimation, and control. These new theoretical tools will be applied to the basic sciences, with a goal of better understanding the human genome and how the brain processes, stores, and communicates information.
Wireless Networks, Sensor Networks, Convergence of Control, Communication and Computation, Semiconductor Manufacturing, Manufacturing Systems, Machine Learning, Adaptive Systems, Control, Stochastic Systems, Information Theory, Middleware, Protocol design, Implementation, Software architecture, Control Theory, Optimization.
Berkeley researchers on the team provide strength in probability, mathematical statistics, computer science, statistical machine learning, information theory, wireless communication, communication networking, computational neuroscience, and systems biology. With their assistance, the SOI team will extend information theory to fields such as networking, statistical modeling of and computation with massive data sets, modeling and data analysis in neuroscience and systems biology, and environmental science.
UC San Diego researchers possess expertise in bioinformatics (the application of information science to molecular biology) and systems biology (the study of complex molecular and cellular networks) - fields that require the integration of engineering, mathematics, computer sciences, physical sciences, and biological sciences. Leveraging these strengths, along with UCSD's proficiency in supercomputing, team members will design biological applications and aid information theorists in developing novel information-theoretical methods.
Research at the University of Hawaii covers theory and practical topics in information theory, statistical learning and signal processing. In particular, a lot of focus is on high dimensional problems, reflecting requirements for diverse applications in data processing, handling biological and genetic data, risk management, channels with memory, and smart grids among others.
Researchers gravitate toward solutions that involve nice combinatorics or probabilistic arguments where possible. During the course of obtaining engineering and statistically relevant solutions, researchers use results and insights from number theory, combinatorics, and topology to name a few seemingly uncommon subject areas.
Illinois researchers will use principles of applied probability, information theory, and control to understand how decentralization, feedback, and dynamics in networks enable complex functions in neurobiological systems, gene regulatory networks, and wireless networks. Long-term, their findings could lead to a greater understanding of the functional architecture of the brain, novel methods for disease treatment, and design principles of next-generation wireless networks. Illinois also will help oversee diversity efforts, encouraging underrepresented groups to take part in scientific research.