Ashwin Renganathan is a member of the Institute for Data Engineering and Science.

Dr. Rehg's research interests include computer vision, computer graphics, machine learning, robotics, and distributed computing. He co-directs the Computational Perception Laboratory (CPL) and is affiliated with the GVU Center, Aware Home Research Institute, and the Center for Experimental Research in Computer Science. In past years he has taught "Computer Vision" (CS 4495/7495) and "Introduction to Probabilistic Graphical Models" (CS 8803). He is currently teaching "Pattern Recognition" (CS 4803) and "Computer Graphics" (CS 4451). Dr. Rehg received the 2005 Raytheon Faculty Fellowship Award from the College of Computing. His paper with Ph.D. student Yushi Jing and collaborator Vladimir Pavlovic was the recipient of a Distinguished Student Paper Award at the 2005 International Conference on Machine Learning. Dr. Rehg currently serves on the Editorial Board of the International Journal of Computer Vision. He was the Short Courses Chair for the International Conference on Computer Vision (ICCV) in 2005 and the Workshops Chair for ICCV 2003. Dr. Rehg consults for several companies and has served as an expert witness. His research is funded by the NSF, DARPA, Intel Research, Microsoft Research, and the Mitsubishi Electric Research Laboratories.

Note: Rehg recently moved to the University of Illinois Urbana-Champaign as the Founder Professor of Computer Science and Industrial and Enterprise Systems Engineering.

Dana Randall is an American computer scientist. She works as the ADVANCE Professor of Computing, and adjunct professor of mathematics at the Georgia Institute of Technology. She is also an External Professor of the Santa Fe Institute. Previously she was executive director of the Georgia Tech Institute of Data Engineering and Science (IDEaS) that she co-founded, and director of the Algorithms and Randomness Center. Her research include combinatorics, computational aspects of statistical mechanics, Monte Carlo stimulation of Markov chains, and randomized algorithms.

Ramprasad joined the School of Materials Science and Engineering at Georgia Tech in February 2018. Prior to joining Georgia Tech, he was the Centennial Term Professor of Materials Science and Engineering at the University of Connecticut. He joined the University of Connecticut in Fall 2004 after a 6-year stint with Motorola’s R&D laboratories at Tempe, AZ. Ramprasad received his B. Tech. in Metallurgical Engineering at the Indian Institute of Technology, Madras, India, an M.S. degree in Materials Science and Engineering at the Washington State University, and a Ph.D. degree also in Materials Science and Engineering at the University of Illinois, Urbana-Champaign.

Ramprasad’s area of expertise is in the development and utilization of computational and data-driven (machine learning) methods aimed at the design and discovery of new materials. Materials classes under study include polymers, metals and ceramics (mainly dielectrics and catalysts), and application areas include energy production and energy storage. Prof. Ramprasad’s research has been funded by the Office of Naval Research (ONR), the National Science Foundation (NSF), the Department of Energy (DOE), the Army Research Office (ARO), and Toyota Research Institute (TRI). He has lead a ONR-sponsored Multi-disciplinary University Research Initiative (MURI) in the past to accelerate the discovery of polymeric capacitor dielectrics for energy storage, and is presently leading another MURI aimed at the understanding and design of dielectrics tolerant to enormous electric fields.

Ramprasad is a Fellow of the American Physical Society, an elected member of the Connecticut Academy of Science and Engineering, and the recipient of the Alexander von Humboldt Fellowship and the Max Planck Society Fellowship for Distinguished Scientists.

Kishore Ramachandran received his Ph.D. in Computer Science from the University of Wisconsin, Madison in 1986, and has been on the faculty of Georgia Tech since then. He led the definition of the curriculum and the implementation for an online MS program in Computer Science (OMSCS) using MOOC technology for the College of Computing, which is currently providing an opportunity for students world-wide (with an enrollment of over 10,000) to pursue a low-cost graduate education in computer science. He has served as the Director of STAR Center from 2007 to 2014, and as the Director of Korean Programs for the College of Computing from 2007 to 2011. Ramachandran has also served as the Chair of the Core Computing Division within the College of Computing. His research interests are in architectural design, programming, and analysis of parallel and distributed systems. Currently, he is leading a project that deals with large-scale situation awareness using distributed camera networks and multi-modal sensing with applications to surveillance, connected vehicles, and transportation. He is the recipient of an NSF PYI Award in 1990, the Georgia Tech doctoral thesis advisor award in 1993, the College of Computing Outstanding Senior Research Faculty award in 1996, the College of Computing Dean's Award in 2003 and 2014, the College of Computing William "Gus'' Baird Teaching Award in 2004, the "Peter A. Freeman Faculty Award" from the College of Computing in 2009 and in 2013, the Outstanding Faculty Mentor Award from the College of Computing in 2014, and became an IEEE Fellow in 2014.

Peng Qiu is a professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech School of Engineering and Emory University School of Medicine. 

His research interests are in the areas of bioinformatics and computational biology, focusing on machine learning, data integration, statistical signal processing, control systems and optimization. 

In particular, he is interested in developing machine learning methods to advance single-cell data science, with applications in characterizing cellular heterogeneity, identifying cancer biomarkers, understanding disease progression, reconstructing gene regulatory networks, etc.