Jacob Abernethy is an Associate Professor in the College of Computing at Georgia Tech. He started his faculty career in the Department of Electrical Engineering and Computer Science at the University of Michigan. He completed his Ph.D. in Computer Science at the University of California at Berkeley, and then spent two years as a Simons postdoctoral fellow at the CIS department at UPenn. Abernethy's primary interest is in Machine Learning, with a particular focus in sequential decision making, online learning, online algorithms and adversarial learning models. He did his Master's degree at TTI-C, and his Bachelor's Degree at MIT.

Nicoleta Serban is the Peterson Professor of Pediatric Research in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Dr. Serban's most recent research focuses on model-based data mining for functional data, spatio-temporal data with applications to industrial economics with a focus on service distribution and nonparametric statistical methods motivated by recent applications from proteomics and genomics. 

She received her B.S. in Mathematics and an M.S. in Theoretical Statistics and Stochastic Processes from the University of Bucharest. She went on to earn her Ph.D. in Statistics at Carnegie Mellon University.

Dr. Serban's research interests on Health Analytics span various dimensions including large-scale data representation with a focus on processing patient-level health information into data features dictated by various considerations, such as data-generation process and data sparsity; machine learning and statistical modeling to acquire knowledge from a compilation of health-related datasets with a focus on geographic and temporal variations; and integration of statistical estIMaTes into informed decision making in healthcare delivery and into managing the complexity of the healthcare system.

Kamran Paynabar is the Fouts Family Early Career Professor and Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He received his B.Sc. and M.Sc. in Industrial Engineering from Iran in 2002 and 2004, respectively, and his Ph.D. in Industrial and Operations Engineering from The University of Michigan in 2012. He also holds an M.A. in Statistics from The University of Michigan. His research interests comprise both applied and methodological aspects of machine-learning and statistical modeling integrated with engineering principles. He is a recipient of the INFORMS Data Mining Best Student Paper Award, the Best Application Paper Award from IIE Transactions, the Best QSR refereed paper from INFORMS, and the Best Paper Award from POMS. He has been recognized with the Georgia Tech campus level 2014 CETL/BP Junior Faculty Teaching Excellence Award and the Provost Teaching and Learning Fellowship. He served as the chair of QSR of INFORMS, and the president of QCRE of IISE.

Enlu Zhou is a professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. She received the B.S. degree with highest honors in electrical engineering from Zhejiang University, China, in 2004, and the Ph.D. degree in electrical engineering from the University of Maryland, College Park, in 2009. Prior to joining Georgia Tech in 2013, she was an assistant professor in the Industrial & Enterprise Systems Engineering Department at the University of Illinois Urbana-Champaign from 2009-2013. She is a recipient of the Best Theoretical Paper award at the Winter Simulation Conference, AFOSR Young Investigator award, NSF CAREER award, and INFORMS Outstanding Simulation Publication Award. She has served as an associate editor for Journal of Simulation, IEEE Transactions on Automatic Control, and Operations Research. She is currently the Vice President and President-Elect of the INFORMS Simulation Society.

Mayya Zhilova is an associate professor in the School of Mathematics at Georgia Tech and an affiliated member of the Machine Learning Center. She received her Ph.D. in statistics from the Humboldt University of Berlin in 2015. 

Her primary research interests lie in the areas of mathematical statistics, statistical learning theory, and uncertainty quantification, particularly in statistical inference for complex high-dimensional data, performance of resampling procedures for various classes of problems, functional estimation, and inference for misspecified models.

Mohit Singh is a Coca-Cola Foundation Professor in the H. Milton Stewart School of Industrial and Systems Engineering and the Director of the Algorithms and Randomness Center (ARC). Prior to this, he served as a researcher in the Theory Group at Microsoft Research in Redmond, Washington.

Singh’s research interests include discrete optimization, approximation algorithms, and convex optimization. His research is focused on optimization problems arising in cloud computing, logistics, network design, and machine learning.

Singh received the Tucker Prize in 2009 given by the Mathematical Optimization Society for an outstanding doctoral thesis on “Iterative Methods in Combinatorial Optimization.” He also received the best paper award for his work on the traveling salesman problem at the Annual Symposium on Foundations of Computer Science (FOCS) in 2011.

Previously, Singh was an assistant professor at McGill University from 2010-2011 and a postdoctoral researcher at Microsoft Research, New England from 2008-2009.

He obtained his Ph.D. in 2008 from the Tepper School of Business at Carnegie Mellon University.

Alexander Shapiro is the A. Russell Chandler III Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. 

Dr. Shapiro’s research interests are focused on stochastic programming, risk analysis, simulation based optimization, and multivariate statistical analysis.   In 2013 he was awarded Khachiyan Prize of INFORMS for lifetime achievements in optimization, and in 2018 he was a recipient of the Dantzig Prize awarded by the Mathematical Optimization Society and Society for Industrial and Applied Mathematics. In 2020 he was elected to the National Academy of Engineering. In 2021 he was a recipient of John von Neumann Theory Prize awarded by the Institute for Operations Research and the Management Sciences (INFORMS). 

Dr. Shapiro served  on editorial board of a number of professional journals. He was an area editor (optimization) of the Operations Research Journal and the editor-in-chief of the Mathematical Programming, Series A, Journal. 

Galyna Livshyts completed her undergraduate studies in Kharkiv, Ukraine. She obtained her PhD from Kent State University in Ohio in 2015 under the supervision of Artem Zvavitch. Since 2015, Galyna has been an assistant professor at the School of Math, Georgia Institute of Technology. In Fall 2017, she was a postdoc at the MSRI program in Geometric Asymptotic Analysis and Applications at MSRI, Berkeley. Galyna is interested in High-dimensional Probability and Convexity, as well as Asymptotic Analysis and Random Matrix Theory.

David Goldsman is the Director of Master's Recruiting and Admissions and Coca-Cola Professor in the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. He received his Ph.D. in 1984 from the School of Operations Research and Industrial Engineering at Cornell University. He also holds degrees from Syracuse University in Mathematics, Physics, and Computer and Information Sciences. He has been a Visiting Professor or Scientist at Cornell University, Syracuse University, The University of North Carolina–Chapel Hill, AT&T Bell Laboratories, NEC USA, The Middle East Technical University, Northwestern University, The University of Oklahoma, Sabancı University, Boğaziçi University, Özyeğin University, Monterrey Tech, and The University of the Andes. 

Dave's research interests include simulation output analysis, statistical ranking and selection methods, and medical and humanitarian applications of operations research. He has published extensively, and has over 75 publications in such bellwether journals as Management Science, Operations Research, Operations Research Letters, IIE Transactions, and Sequential Analysis. He has also co-authored about 20 book chapters as well as the texts Design and Analysis of Experiments for Statistical Selection, Screening and Multiple Comparisons, with Bob Bechhofer and Tom Santner, and Probability and Statistics in Engineering (4th edition), with Bill Hines, Doug Montgomery, and Connie Borror. 

Dave is an Associate Editor for Sequential Analysis and the Journal of Simulation. He was previously the Simulation Department Editor for IIE Transactions and an Associate Editor for Operations Research Letters. He was also the Associate Editor for the Proceedings of the 1992 Winter Simulation Conference (WSC), the Program Chair for the 1995 WSC, and the IIE Board Representative to the WSC (2001–2009). Further, he has served in various elected positions for the INFORMS Simulation Society, including President. He was the Chair of the INFORMS Public Awareness Committee from 2002–2008, and has engaged in substantial outreach to high school and community college students and teachers for over 25 years. 

Dave and Christos Alexopoulos won the INFORMS Simulation Society's 2007 Outstanding Simulation Publication Award for their paper “To Batch or not to Batch?” which appeared in ACM TOMACS in 2004. In addition, Dave, Christos, Claudia Antonini, and Jim Wilson won the IIE Transactions 2010 Best Paper Prize in Operations Engineering and Analysis for their 2009 paper “Area Variance Estimators for Simulation Using Folded Standardized Time Series.” Dave received the INFORMS Simulation Society's Distinguished Service Award in 2002. He also received a Fulbright fellowship in 2006 to lecture at Boğaziçi and Sabancı Universities in Istanbul, Turkey. Dave is a Fellow of the Institute of Industrial Engineers. 

Dave is an active consultant, having undertaken various projects in the healthcare, airline, automotive, fast food, hotel, and banking industries, among others.