Prof. Burton Rosenberg - Financial Cryptography

Prof. Rosenberg researches Financial Cryptography. Financial Cryptography is a field that bridges theoretical cryptography and practical security in order to translate social ceremonies into cyber space and create culturally significant cyber assets. This includes bitcoin systems, systems of voting, identity and trust, and various information hiding, revealing, and authenticating technologies. While Prof. Rosenberg's research focuses on the technical, the research of necessity connects with economic, sociological, political, and legal questions. Prof. Rosenberg is the editor in chief of Financial Cryptography, Chapman & Hall/CRC Press, 2010, and a director of IFCA, the International Financial Cryptography Association.

Prof. Odelia Schwartz - Computational Neuroscience

Prof. Schwartz's research is at the interface of computer science and the brain sciences. She is interested in understanding how the brain makes sense of information in the environment, resulting in complex inferences, perception, and behavior. This understanding could lead to artificial intelligence systems that are more compatible with human cognition, and to approaches for treating brain functions. It's now a particularly exciting time to advance such questions, due to progress in machine learning and deep learning, and the availability of experimental neuroscience and psychology data. Therefore, she is building computer models of neural processing in the brain, and collaborating with experimental groups. She has received funding from the NSF, the NIH, a Google faculty research award, the Army Research Office, and an Alfred P. Sloan Research Fellowship.

Prof. Geoff Sutcliffe - Automated Reasoning

Prof. Sutcliffe is the developer and provides ongoing maintenance of the TPTP World, that provides standards, test problems, solutions to those problems, and infrastructure for evaluating classical logic automated reasoning systems. Associated with the TPTP World, Prof. Sutcliffe runs the CADE ATP System Competition - the world championship for classical logic automated reasoning systems. More details about the TPTP World and the competition can found starting at Prof. Sutcliffe is also one of the leaders of the StarExec project that provides computing infrastructure to logic-solving communities, to facilitate the experimental evaluation of logic solvers. StarExec can be accessed at and

Prof. Zheng Wang - Bioinformatics

Prof. Zheng Wang's research interest is in bioinformatics. Bioinformatics is a field in which computer science technologies are used to solve biological problems. Prof. Zheng Wang's lab is working on the reconstruction of genome 3D structures, family classification of topologically associating domains, enhancement of Hi-C data resolution, prediction of protein functions, prediction of protein structures, and analysis of biological complex networks. Prof. Zheng Wang collaborates with cancer scientists, neuroscientists, and biologists to work on research problems in life science and medical fields. Deep learning, optimization, Metropolis-Hastings simulation, Hidden Markov Model, graph kernel, graph alignment, and graph convolutional networks are the representative algorithms used in Prof. Zheng Wang's research. More details about the research of Prof. Zheng Wang can be found at