Sudheer Chava, Ph.D, is an associate director of the Institute for Information Security & Privacy for the area of risk management, and professor of finance at Scheller College of Business at the Georgia Institute of Technology. He also serves as finance area coordinator at Scheller and as the director of the nationally top 10 ranked Master of Science in Quantitative and Computational Finance (QCF) program at Georgia Tech (a joint program by the School of Mathematics, Industrial and Systems Engineering, and Scheller).  Dr. Chava has taught a variety of courses at the undergraduate, masters, MBA and Ph.D. levels, including derivatives, risk management, valuation, credit risk, financial technology ("fintech"), and management of financial institutions. He also has taught both theoretical and empirical finance doctoral courses and is a faculty advisor to multiple doctoral students. Dr. Chava's main research interests are risk management, credit risk and financial institutions. He has extensively published on these topics in the leading finance journals such as the Journal of Finance, Journal of Financial Economics, Review of Financial Studies, Journal of Monetary Economics, Journal of Financial and Quantitative Analysis, and Management Science. His research won a Ross Award for the best paper published in Finance Research Letters in 2008, was a finalist for the Brattle Prize for the best paper published in Journal of Finance in 2008, and was nominated for the Goldman Sachs Award for the best paper for published in Review of Finance during 2004.  Dr. Chava is the recipient of multiple external research grants such as FDIC-CFR Fellowship, Morgan Stanley Research grant, Financial Service Exchange Research grant, Q-group Research Award (2010, 2012) and GARP Research Award. He has presented his research at finance conferences such as AFA, WFA, EFA, Federal Reserve Banks and at many universities in the United States and abroad. Chava received his Ph.D. from Cornell University in 2003. Prior to that he earned an MBA degree from the Indian Institute of Management – Bangalore, an undergraduate degree in Computer Science Engineering, and worked as a fixed-income analyst at a leading investment bank in India. In 2014, he was awarded the Linda and Lloyd L. Byars Award for faculty research excellence at Georgia Tech and he has also received multiple research awards and fellowships at Texas A&M University.

Ümit V. Çatalyürek is currently a Professor and the Associate Chair of the School of Computational Science and Engineering in the College of Computing at the Georgia Institute of Technology. Prior joining Georgia Institute of Technology, he was a Professor and Vice Chair of the Department of Biomedical Informatics, and Professor in the Departments of Electrical & Computer Engineering, and Computer Science & Engineering at the Ohio State University. He received his Ph.D., M.S. and B.S. in Computer Engineering and Information Science from Bilkent University, Turkey, in 2000, 1994 and 1992, respectively. 

Dr. Çatalyürek is a Fellow of IEEE and SIAM. He was the elected Chair for IEEE TCPP for 2016-2019, and currently serves as Vice-Chair for ACM SIGBio for 2015-2021 terms. He also serves as the member of Board of Trustees of Bilkent University. 

He currently serves as the Editor-in-Chief for Parallel Computing. In the past, he also served on the editorial boards of the IEEE Transactions on Parallel and Distributed Computing Systems, the SIAM Journal of Scientific Computing, Journal of Parallel and Distributed Computing, and Network Modeling and Analysis in Health Informatics and Bioinformatics. He also serves on the program committees and organizing committees of numerous international conferences. 

A recipient of an NSF CAREER award, Dr. Çatalyürek is the primary investigator of several awards from the Department of Energy, the National Institute of Health, and the National Science Foundation. He has co-authored more than 200 peer-reviewed articles, invited book chapters and papers. His main research areas are in parallel computing, combinatorial scientific computing and biomedical informatics.

Since the fall of 2000, Robert has taught several courses in the College of Management at the Bachelors, Masters and Executive Masters levels. Quantitative course experience includes Analytic Tools (statistics, regression analysis and simulation) and Management Science (linear programming, network models, decision analysis, queuing models, project scheduling and simulation). Experience teaching qualitative (case-based) courses include Operations Management, Service Operations Management and Management of Technology. He has won several student-elected teaching awards including College of Management Undergraduate Professor of the Year (2001, 2004 and 2007), MBA Elective Professor or the Year (Service Operations – 2003), MBA Core Professor of the Year (Analytic Tools – 2008) and Evening MBA Elective Professor or the Year (Management of Technology – 2011). 

Prior teaching experience includes four years at the Georgia State University Robinson College of Business where he taught MBA-level courses in Operations Management, Project Management, Operations Strategy, Global Operations Management and Applications of Simulation in Management. 

Current research interests include empirical research in Service industries, outsourcing in both manufacturing and service industries, and applications of evidence based management techniques. He is a co-author of two published papers and a case study and has several working papers in various stages of completion. He has made 22 technical presentations at academic conferences since 1994. 

Educational background includes a BS in Engineering Science from the University of Tennessee – Knoxville, an MBA from Lynchburg College (Virginia) and he has completed three of four parts of a PhD in Operations Management from Georgia Tech College of Management (ABD-All but Dissertation). 

Eight years of professional experience prior to academics includes jet engine structural design engineer at Pratt & Whitney Aircraft (West Palm Beach, FL) and as a product engineer and then an engineering manager at Babcock & Wilcox – Naval Nuclear Fuel Division (Lynchburg, VA).

Pam Buffington is the executive director of Foundational Infrastructure & Technology within the Office of Information Technology (OIT). Pam has extensive experience at Georgia Tech and has worked in a variety of roles and responsibilities since 1995, enabling innovative uses of information technologies in both research and academic/instructional capacities. Most recently, she served as director of Research Cyberinfrastructure & Computing – guiding the work of the Partnership for an Advanced Computing Environment – or PACE. PACE is a collaboration between Georgia Tech faculty and OIT with a focus on high performance computing infrastructure with technical support services. Prior to her time leading PACE, Pam led OIT’s Digital Learning Team as associate director of Academic Technologies and steered external relations activities for Center for 21st Century Universities, or C21U.  

Pam is also a published researcher who most recently co-authored Semi-Automatic Hybrid Software Deployment Workflow in a Research Computing Center. An official “Double Jacket,” Pam earned both her undergraduate (BS’95) and Master of Business Administration (MBA ’23) degrees from Georgia Tech. 

Sam Brown's lab studies the multi-scale dynamics of infectious disease. Their goal is to improve the treatment and control of infectious diseases through a multi-scale understanding of microbial interactions. Their approach is highly interdisciplinary, combining theory and experiment, evolution, ecology and molecular microbiology in order to understand and control the multi-scale dynamics of bacteria pathogens.

Dr. Annalisa Bracco is a professor at Georgia Tech with extensive background in computational fluid dynamics and physical oceanography. Her research interests include coastal ocean circulation, with focus on meso- and submesoscale processes, ocean predictability and inverse dynamics, impacts of physical forcing on ecosystems, and climate model validation. Her group has been involved in field collections during the Deepwater Horizon spill (July/Aug. 2010) and was back in the Gulf in the summer of 2011.

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.