Dr. Duke has led over $21 million in funded research for industry, government, and foundation partners. Dr. Duke’s research focuses on advancing techniques for identifying patients of interest from diverse data sources with applications spanning research, quality, and clinical domains. He led the Merck-Regenstrief Partnership in Healthcare Innovation and was a founding member of OHDSI, an open-source international health data analytics collaborative. In addition to numerous peer-reviewed publications, his work has been featured in the lay media including the New York Times, NPR, and MSNBC. Dr. Duke completed his medical degree at Harvard Medical School and a master's in human-computer interaction at Indiana University.

Joel Sokol is the Harold E. Smalley Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He is also Director of the interdisciplinary Master of Science in Analytics degree (on-campus and online).

His primary research interests are in sports analytics and applied operations research. He has worked with teams or leagues in all three of the major American sports. Dr. Sokol's LRMC method for predictive modeling of the NCAA basketball tournament is an industry leader, and his non-sports research has won the EURO Management Science Strategic Innovation Prize and been a finalist for the Cozzarelli Prize.

Dr. Sokol has also won recognition for his teaching and curriculum development from IIE and the NAE, held the Fouts Family Associate Professorship for a three-year term, and is the recipient of Georgia Tech's highest awards for teaching. He served two terms as INFORMS Vice President of Education, and is a past Chair and founding officer of the INFORMS section on sports operations research.

Dr. Sokol's Ph.D. in operations research is from MIT, and his bachelor's degrees in mathematics, computer science, and applied sciences in engineering are from Rutgers University.

I am currently a Senior Research Scientist at Georgia Tech working in the School of Computer Science in the College of Computing since 2015. Previously, I have worked as as a research scientist in the School of Computational Science and Engineering (CSE) from 2013 to 2015. This work focused on advanced user support and benchmarking for the Keeneland project and investigating architecture-related research topics for Dr. Jeff Vetter’s Future Technologies Group at Oak Ridge National Lab.

With a background in computer architecture, my main research interests are focused on the intersection of high-performance computing and novel accelerators including GPUs, Xeon Phi, FPGAs, and Arm SVE processors. I am currently working on a collaborative research program for near-memory computing with High Bandwidth Memory (HBM) for processors and GPUs, SuperSTARLU, which is funded by the NSF. I am co-director of Georgia Tech’s Center for High Performance Computing, and I am also the director of a novel architecture testbed, the CRNCH Rogues Gallery, that aims to simplify and democratize access to novel post-Moore accelerators in the neuromorphic, reversible, and novel networking spaces.

I defended my PhD in August 2013 in the area of computer architecture working under Dr. Sudhakar Yalamanchili. More information on this networks- and memory-related research can be found under the publications tab.

Dr. Gari Clifford is a tenured Professor of Biomedical Informatics and Biomedical Engineering at Emory University and the Georgia Institute of Technology, and the Chair of the Department of Biomedical Informatics (BMI) at Emory. His research focuses on the application of signal processing and machine learning to medicine to classify, track and predict health and illness. His focus research areas include critical care, digital psychiatry, global health, mHealth, neuroinformatics and perinatal health. After training in Theoretical Physics, he transitioned to AI and Engineering for his doctorate (DPhil) at the University of Oxford in the 1990’s. He subsequently joined MIT as a postdoctoral fellow, then Principal Research Scientist where he managed the creation of the MIMIC II database, the largest open access critical care database in the world. He later returned as an Associate Professor of Biomedical Engineering to Oxford, where he helped found its Sleep & Circadian Neuroscience Institute and served as Director of the Centre for Doctoral Training in Healthcare Innovation at the Oxford Institute of Biomedical Engineering. As Chair, Dr Clifford has established BMI as a leading center for critical care and mHealth informatics, and as a champion for open access data and open source software in medicine, particularly through his leadership of the PhysioNet/CinC Challenges and contributions to the PhysioNet Resource. Despite this, he is a strong supporter of commercial translation, working closely with industry, and serves as CTO of MindChild Medical, a spin out from his research at MIT.

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.

His areas of expertise include optimization theory and applications. His recent research activities deal with issues arising in radiation therapy treatment planning and supply chain management. In radiation therapy treatment planning, his main goal has been to develop new models and algorithms for efficiently determining effective treatment plans for cancer patients who are treated using radiation therapy, and treatment schedules for radiation therapy clinics. In supply chain optimization, his main interests are in the integrated optimization of production, inventory, and transportation processes, in particular in the presence of demand flexibility, limited resources, perishability, and uncertainty.

He previously served as Program Director for the Manufacturing Enterprise Systems, Service Enterprise Systems, and Operations Research programs at the National Science Foundation, and as Professor and Richard C. Wilson Faculty Scholar in the Department of Industrial and Operations Engineering at the University of Michigan. Before joining the University of Michigan in 2008, he was on the faculty of the Department of Industrial and Systems Engineering at the University of Florida and the Rotterdam School of Management at the Erasmus University Rotterdam in The Netherlands. 

He is a Fellow of the Institute of Operations Research and the Management Sciences (INFORMS) and the Institute of Industrial & Systems Engineers (IISE), and a member of the Mathematical Optimization Society (MOS), Society of Industrial and Applied Mathematics (SIAM), and the American Association of Physicists in Medicine (AAPM).

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. 

Dr. Tovey's principal research and teaching activities are in operations research and its interdisciplinary applications to social and natural systems, with emphasis on sustainability, the environment, and energy. His current research concerns inverse optimization for electric grid management, classical and biomimetic algorithms for robots and webhosting, the behavior of animal groups, sustainability measurement, and political polarization.  

Dr. Tovey received a Presidential Young Investigator Award in 1985 and the 1989 Jacob Wolfowitz Prize for research in heuristics. He was granted a Senior Research Associateship from the National Research Council in 1990, was named an Institute Fellow at Georgia Tech in 1994, and received the Class of 1934 Outstanding Interdisciplinary Activity Award in 2011. In 2016, Dr. Tovey was recognized by the ACM Special Interest Group on Electronic Commerce with the Test of Time Award for his work as co-author of the paper “How Hard Is It to Control an Election?” He was a 2016 Golden Goose Award recipient for his role on an interdisciplinary team that studied honey bee foraging behavior which led to the development of the Honey Bee Algorithm to allocate shared webservers to internet traffic. 

Dr. Tovey received an A.B. in applied mathematics from Harvard College in 1977 and both an M.S. in computer science and a Ph.D. in operations research from Stanford University in 1981. 

Chao Zhang is an Assistant Professor at the School of Computational Science and Engineering, Georgia Institute of Technology. His research area is data mining, machine learning, and natural language processing. His research aims to enable machines to understand text data in more label-efficient and robust way in open-world settings. Specific research topics include weakly-supervised learning, out-of-distribution generalization, interpretable machine learning, and knowledge extraction and reasoning. He is a recipient of Google Faculty Research Award, Amazon AWA Machine Learning Research Award, ACM SIGKDD Dissertation Runner-up Award, IMWUT distinguished paper award, and ECML/PKDD Best Student Paper Runner-up Award. Before joining Georgia Tech, he obtained his Ph.D. degree in Computer Science from University of Illinois at Urbana-Champaign in 2018.

Matt is a former Tar Heel from UNC Chapel Hill. His training is in mass spectrometry-based proteomics and G protein signaling. He has been investigating PTMs since 2001. He is also a co-director of the Systems Mass Spectrometry Core (SYMS-C) facility at Georgia Tech.