Hannah Choi is an Assistant Professor in the School of Mathematics at Georgia Tech. Her research focuses on mathematical approaches to neuroscience, with primary interests in linking structures, dynamics, and computation in data-driven brain networks at multiple scales. Before coming to Georgia Tech, she was a postdoctoral fellow at the University of Washington and also a visiting scientist at the Allen Institute for Brain Science, and spent one semester at the Simons Institute for the Theory of Computing at the University of California, Berkeley as a Patrick J McGovern Research Fellow. She received her Ph.D. in Applied Mathematics from Northwestern University and her BA in Applied Mathematics from the University of California, Berkeley.

Dr. Fan Zhang received her Ph.D. in Nuclear Engineering and M.S. in Statistics from UTK in 2019. She is the recipient of the 2021 Ted Quinn Early Career Award from the American Nuclear Society and joined the Woodruff School in July, 2021. She is actively involved with multiple international collaborations on improving nuclear cybersecurity through the International Atomic Energy Agency (IAEA) and the DOE Office of International Nuclear Security (INS). Dr. Zhang’s research primarily focuses on the cybersecurity of nuclear facilities, online monitoring & fault detection using data analytics methods, instrumentation & control, and nuclear systems modeling & simulation. She has developed multiple testbeds using both simulators and physical components to investigate different aspects of cybersecurity as well as process health management.

Tom Conte holds a joint appointment in the Schools of Electrical & Computer Engineering and Computer Science at the Georgia Institute of Technology. He is the founding director of the Center for Research into Novel Computing Hierarchies (CRNCH). His research is in the areas of computer architecture and compiler optimization, with emphasis on manycore architectures, microprocessor architectures, back-end compiler code generation, architectural performance evaluation and embedded computer system architectures.

Pascal Van Hentenryck is an A. Russell Chandler III Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Prior to this appointment, he was a professor of Computer Science at Brown University for about 20 years, he led the optimization research group (about 70 people) at National ICT Australia (NICTA) (until its merger with CSIRO), and was the Seth Bonder Collegiate Professor of Engineering at the University of Michigan. Van Hentenryck is also an Honorary Professor at the Australian National University.

Van Hentenryck is a Fellow of AAAI (the Association for the Advancement of Artificial Intelligence) and INFORMS (the Institute for Operations Research and Management Science). He has been awarded two honorary doctoral degrees from the University of Louvain and the university of Nantes, the IFORS Distinguished Lecturer Award, the Philip J. Bray Award for teaching excellence in the physical sciences at Brown University, the ACP Award for Research Excellence in Constraint Programming, the ICS INFORMS Prize for Research Excellence at the Intersection of Computer Science and Operations Research, and an NSF National Young Investigator Award. He received a Test of Time Award (20 years) from the Association of Logic Programming and numerous best paper awards, including at IJCAI and AAAI. Van Hentenryck has given plenary/semi-plenary talks at the International Joint Conference on Artificial Intelligence (twice), the International Symposium on Mathematical Programming, the SIAM Optimization Conference, the Annual INFORMS Conference, NIPS, and many other conferences. Van Hentenryck is program co-chair of the AAAI’19 conference, a premier conference in Artificial Intelligence.

Van Hentenryck’s research focuses in Artificial Intelligence, Data Science, and Operations Research. His current focus is to develop methodologies, algorithms, and systems for addressing challenging problems in mobility, energy systems, resilience, and privacy. In the past, his research focused on optimization and the design and implementation of innovative optimization systems, including the CHIP programming system (a Cosytec product), the foundation of all modern constraint programming systems and the optimization programming language OPL (now an IBM Product). Van Hentenryck has also worked on computational biology, numerical analysis, and programming languages, publishing in premier journals in these areas.

Van Hentenryck runs the Seth Bonder summer Camp in Computational and Data Science for middle- and high-school students every summer. 

Dr. Shihao Yang is an assistant professor in the School of Industrial & Systems Engineering at Georgia Tech. Prior to joining Georgia Tech, he was a post-doc in Biomedical Informatics at Harvard Medical School after finishing his PhD in statistics from Harvard University. Dr. Yang’s research focuses on data science for healthcare and physics, with special interest in electronic health records causal inference and dynamic system inverse problems.

Xu Chu is an assistant professor in the School of Computer Science at Georgia Tech. He obtained his Ph.D. degree from the University of Waterloo in late 2017, and joined Georgia Tech in Jan 2018. He is a recipient of the JP Morgan Faculty Research Fellow Award, the Microsoft Ph.D. fellowship award, and the David R. Cheriton fellowship award. 

He is broadly interested in data management systems and machine learning. In particular, he focuses on (1) how to leverage advanced machine learning techniques to solve hard and practical data management problems, such as large-scale data integration; and (2) how to build data management systems to tackle the common pain points in practical machine learning, such as the lack of high-quality labeled data.

Keith Werle is Managing Director of the Business Analytics Center and a Professor of the Practice in Georgia Tech Scheller College of Business. 

With over thirty years of experience in industry and consulting, his background spans a broad range of business disciplines including finance, analytics, strategy, and corporate development. He has consulted in many industries and for a diverse range of clients, from venture capital backed technology start-ups to global Fortune 50 companies. His client work focused on business analytics and the application of advanced data visualization, multi-dimensional performance analysis, data mining and machine learning techniques in strategy development, decision support, and operations management.

Dr. Felix J. Herrmann is Georgia Research Alliance Eminent Scholar in Energy and a professor at the Georgia Institute of Technology with appointments in the Schools of Earth and Atmospheric Sciences, Computational Science and Engineering, and Electrical and Computer Engineering. Dr. Herrmann will be the 2019 Distinguished Lecturer of the Society of Exploration Geophysicists (SEG). 

Dr. Herrmann holds a M.Sc. and Ph.D. in Engineering Physics from the Delft University of Technology. He completed his postdoctoral studies at Stanford University and MIT before becoming a professor at the University of British Columbia's Department of Earth, Ocean, and Atmospheric Sciences. He joined the faculty of the Georgia Institute of Technology in October 2017. 

During his career, Dr. Herrmann has worked on the development of the next-generation of industrial acquisition and computational imaging technologies designed to improve the image quality in complex geological areas at vastly reduced costs and environmental impact. Aside from driving innovations, by leveraging recent developments in the mathematical and computational sciences, Dr. Herrmann has extensive experience working with industry. At the University of British Columbia, he was the founder and director of the Seismic Laboratory for Imaging and Modelling (SLIM), which hosted the industry Consortium SINBAD. Under his guidance, SLIM became a world leader in the successful integration of transformative scientific developments, such as compressive sensing, randomized linear algebra, and machine learning, into innovative approaches that tackle the most challenging imaging problems. With his move to the Georgia Institute of Technology, Dr. Herrmann plans to broaden his research program to include other imaging modalities. Dr. Herrmann was a long program participant at UCLA's Institute for Pure and Applied Mathematics in the Fall of 2004 and has been involved in public-private partnerships around the world. He serves on the editorial board of Geophysical Prospecting and on the SEG Research Committee.

Chris Gu is an Assistant Professor of Marketing in the Scheller College of Business at Georgia Institute of Technology. His research focuses on the quantitative study of the behaviors of individuals and organizations under various types of information constraints and economic structures, with the goal of improving their well-being. His current work focuses on understanding how consumers search for products under partially revealed information, how consumers adopt sustainable technologies under the influence of government policies, how companies decide about internal technology adoption and upgrade, and how social network connections influence individual crowdsourcing behaviors. He is an AMS Mary Kay Foundation Doctoral Dissertation Competition Finalist, and his research has received the ISMS Doctoral Dissertation Award.

Arkadi Nemirovski is the John P. Hunter, Jr. Chair in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. 

Dr. Nemirovski's research interests focus on Optimization Theory and Algorithms, with emphasis on investigating complexity and developing efficient algorithms for nonlinear convex programs, optimization under uncertainty, applications of convex optimization in engineering, and nonparametric statistics. 

Dr. Nemirovski has made fundamental contributions in continuous optimization in the last thirty years that have significantly shaped the field. In recognition of his contributions to convex optimization, Nemirovski was awarded the 1982 Fulkerson Prize from the Mathematical Programming Society and the American Mathematical Society (joint with L. Khachiyan and D. Yudin), the Dantzig Prize from the Mathematical Programming Society and the Society for Industrial and Applied Mathematics in 1991 (joint with M. Grotschel). He was elected a Member of the National Academy of Engineering (2017) and a Fellow of the American Academy of Arts and Sciences (2018). 

In recognition of his seminal and profound contributions to continuous optimization, Nemirovski was awarded the 2003 John von Neumann Theory Prize by the Institute for Operations Research and the Management Sciences (along with Michael Todd). He He continues to make significant contributions in almost all aspects of continuous optimization: complexity, numerical methods, stochastic optimization, and non-parametric statistics. 

Dr. Nemirovski earned a Ph.D. in Mathematics (1974) from Moscow State University, the Doctor of Sciences in Mathematics (1990) from the Supreme Attestation Board at the USSR Council of Ministers, and the Doctor of Mathematics (Honoris Causa) from the University of Waterloo, Canada (2009).