Santosh Vempala is a prominent computer scientist. He is a Distinguished Professor of Computer Science at the Georgia Institute of Technology. His main work has been in the area of Theoretical Computer Science. 

Vempala secured B.Tech. degree in Computer Science and Engineering from Indian Institute of Technology, Delhi, in 1992 then he attended Carnegie Mellon University, where he received his Ph.D. in 1997 under professor Avrim Blum. 

Edwin Romeijn is the H. Milton and Carolyn J. Stewart School Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

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.

Craig Tovey is a Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He also co-directs CBID, the Georgia Tech Center for Biologically Inspired Design. 

Dimitri Mavris is a Regents’ Professor, Boeing Professor of Advanced Aerospace Systems Analysis, and an S.P. Langley Distinguished Professor. He also serves as the director of the Aerospace Systems Design Laboratory (ASDL) and executive director of the Professional Master’s in Applied Systems Engineering (PMASE). Dr. Mavris received his B.S., M.S., and Ph.D. in aerospace engineering from the Georgia Institute of Technology.

Dr. Deo came to Georgia Tech in August 2007 as an Assistant Professor of Nuclear and Radiological Engineering. Prior, he was a postdoctoral research associate in the Materials Science and Technology Division of the Los Alamos National Laboratory. He studied radiation effects in structural materials (iron and ferritic steels) and nuclear fuels (uranium dioxide). He also obtained research experience at Princeton University (Mechanical Engineering), Lawrence Livermore National Laboratory, and Sandia National Laboratories.

Dr. Borodovsky and his group develop machine learning algorithms for computational analysis of biological sequences: DNA, RNA and proteins. Our primary focus is on prediction of protein-coding genes and regulatory sites in genomic DNA. Probabilistic models play an important role in the algorithm framework, given the probabilistic nature of biological sequence evolution.