Jye-Chyi (JC) Lu is a professor in in the Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Tech (GT).

Dr. Lu is active in promoting research, education and extension-service programs with focus on engineering statistics and analytics areas. Dr. Lu received a Ph.D. in statistics from University of Wisconsin at Madison in 1988, and joined the statistics faculty of North Carolina State University, where he remained until 1999 when he joined GT-ISyE. He has 82 journal publications in engineering and statistics journals. Twenty seven Ph.D. students has graduated under his supervision.  His research has been supported by many NSF awards and industry grants. He serves as an associate editor (AE) for the Journal of Quality Technology and had served as AEs for Technometrics and IEEE Transactions on Reliability.  He is a Fellow in the American Statistical Association, and has been INFORMS Quality, Statistics and Reliability section chair.

Jing Li is a Virginia C. and Joseph C. Mello Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering and a core faculty in the Center for Machine Learning at Georgia Tech. Prior to joining Georgia Tech in 2020, she was a Professor at Arizona State University and is a co-founder of the ASU-Mayo Clinic Center for Innovative Imaging.

Dr. Li’s research develops statistical machine learning algorithms for modeling and inference of complex-structured datasets with high dimensionality (e.g., 3D/4D images), multi-modality, and  heterogeneity. The objectives of the methodological developments are to provide capacities for monitoring & change detection, diagnosis, and prediction & prognosis. The application domains mainly include health and medicine, focusing on medical image data analytics as well as fusion of images, genomics, and clinical records for personalized and precision medicine. Her research outcomes support clinical decision making for diagnosis, prognosis, and telemedicine for various conditions affecting the brain, such as brain cancer, post-traumatic headache & migraine, traumatic brain injury, and the Alzheimer’s disease. Her research received Best Paper awards from various professional venues such as IISE Transactions, IISE Annual Conferences, INFORMS Data Mining and Decision Analytics, American Academy of Neurology, America Headache Society, etc. Her research has been funded by the NIH, NSF, DOD, and industries. She is an NSF CAREER Awardee.

Dr. Li is a former Chair for the Data Mining Subdivision of INFORMS. She is currently a Senior Editor for IEEE Transactions on Automation Science and Engineering and a Department Editor for IISE Transactions on Healthcare Systems Engineering.

George Lan is an A. Russell Chandler III Professor of Industrial and Systems Engineering at Georgia Institute of Technology.  His research and teaching interests lie in theory, algorithms and applications of stochastic optimization and nonlinear programming.  Most of his current research concerns the design of efficient algorithms for solving challenging optimization problems, especially those arising from data analytics, machine learning, and reinforcement learning. He is actively pursuing the applications of these methodologies in healthcare and sustainability areas. Dr. Lan serves as the associate editor for Computational Optimization and Applications (2014 – present), Mathematical Programming (2016 – present) and SIAM Journal on Optimization (2016  – present). Dr. Lan is an associate director for the center of machine learning at Georgia Tech.

Pinar Keskinocak 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. She is also co-founder and director of the Center for Health and Humanitarian Systems. Previously, she served as the College of Engineering ADVANCE Professor and as interim associate dean for faculty development and scholarship. Prior to joining Georgia Tech, she worked at IBM T.J. Watson Research Center. She received her Ph.D. in Operations Research from Carnegie Mellon University, and her M.S. and B.S. in Industrial Engineering from Bilkent University.

Keskinocak's research focuses on the applications of operations research and management science with societal impact, particularly health and humanitarian applications, supply chain management, and logistics/transportation. Her recent work has addressed infectious disease modeling (including Covid-19, malaria, Guinea worm, pandemic flu), evaluating intervention strategies, and resource allocation; catch-up scheduling for vaccinations; hospital operations management; disaster preparedness and response (e.g., prepositioning inventory); debris management; centralized and decentralized price and lead time decisions. She has worked on projects with companies, governmental and non-governmental organizations, and healthcare providers, including American Red Cross, CARE, Carter Center, CDC, Children’s Healthcare of Atlanta, Emory University, and Intel Corporation.

She is an INFORMS Fellow and currently serves as the president of INFORMS. Previously she served as the Secretary of INFORMS, a department editor for Operations Research (Policy Modeling and Public Sector area), associate editor for Manufacturing & Service Operations Management, and INFORMS Vice President of Membership and Professional Recognition. She is the co-founder and past-president of INFORMS Section on Public Programs, Service, and Needs, and the president of the INFORMS Health Applications Society.

Roshan Vengazhiyil Joseph is a A. Russell Chandler III Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Dr. Joseph's research interests are in the broad areas of applied and computational statistics. A major focus of his research is in developing novel data analytic methods for solving complex engineering problems. He has several years of consulting experience in solving quality-related problems in industries.

Dr. Joseph's honors include Distinguished Dissertation Award from the University of Michigan in 2003, CAREER Award from National Science Foundation in 2005, Jack Youden Prize from ASQ in 2005, Coca-Cola Junior Chair Professorship from ISYE in 2008, Best Paper Award from IIE Transactions in 2009, Franz Edelman Laureate from INFORMS in 2017, Statistics in Physical & Engineering Sciences Award from ASA in 2019, SPAIG Award from the ASA in 2020, and Lloyd S. Nelson Award from ASQ in 2021. He is a Fellow of ASA (elected in 2012) and ASQ (elected in 2020). Currently he is serving as the Editor of Technometrics (2020-2022).

Dr. Joseph received a Ph.D. degree in Statistics from the University of Michigan, Ann Arbor in 2002 and holds an M.Tech. degree in Quality, Reliability, and Operations Research and a B.Tech. degree in Production Engineering and Management. 

Xiaoming Huo is an A. Russell Chandler III Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Dr. Huo's research interests include statistical theory, statistical computing, and issues related to data analytics. He has made numerous contributions on topics such as sparse representation, wavelets, and statistical problems in detectability. His papers appeared in top journals, and some of them are highly cited. He is a senior member of IEEE since May 2004. 

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.

Professor Nagi Gebraeel is the Georgia Power Early Career Professor and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He received his MS and PhD from Purdue University in 1998 and 2003, respectively.

Dr. Gebraeel's research interests lie at the intersection of Predictive Analytics and Machine Learning in IoT enabled maintenance, repair and operations (MRO) and service logistics. His key focus is on developing fundamental statistical learning algorithms specifically tailored for real-time equipment diagnostics and prognostics, and optimization models for subsequent operational and logistical decision-making in IoT ecosystems. Dr. Gebraeel also develops cyber-security algorithms intended to protect IoT-enabled critical assets from ICS-type cyberattacks (cyberattacks that target Industrial Control Systems). From the standpoint of application domains, Dr. Gebraeel has general interests in manufacturing, power generation, and service-type industries. Applications in Deep Space missions are a recent addition to his research interests, specifically, developing Self-Aware Deep Space Habitats through NASA's HOME Space Technology Research Institute.

Dr. Gebraeel leads Predictive Analytics and Intelligent Systems (PAIS) research group at Georgia Tech's Supply Chain and Logistics Institute. He also directs activities and testing at the Analytics and Prognostics Systems laboratory at Georgia Tech's Manufacturing Institute. Formerly, Dr. Gebraeel served as an associate director at Georgia Tech's Strategic Energy Institute (from 2014 until 2019) where he was responsible for identifying and promoting research initiatives and thought-leadership at the intersection of Data Science and Energy applications. He was also the former president of the Institute of Industrial and Systems Engineers (IISE) Quality and Reliability Engineering Division, and is currently a member of the Institute for Operations Research and the Management Sciences (INFORMS), and IISE (since 2005).

Alan Erera is a Manhattan Associates/Dabbiere Chair and the Associate Chair for Research in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He is also the faculty director for the M.S. in Supply Chain Engineering program, Co-Director for Global Transportation in the Supply Chain & Logistics Institute, and Co-Executive Director of the Georgia Tech Panama Logistics Innovation & Research Center.

His research focuses on transportation and logistics systems planning and control, with an emphasis on planning under uncertainty and real-time operational control.  His recent work has addressed dynamic vehicle routing systems for same-day distribution; resilient logistics network design for food supply chains; service network design, linehaul equipment management, and driver scheduling for consolidation freight carriers; robust container fleet management for global shipping companies; and robust and flexible vehicle routing system planning and control for distribution companies. He has written extensively in these subject areas, and has delivered over 100 technical presentations and invited lectures. His research program has been supported by federal agencies (DHS, USDOT, NSF) and major U.S. freight carriers and manufacturing firms.

He received his B.S. Eng. from Princeton University, and his Ph.D. from the University of California, Berkeley.