Irfan Essa is a Professor in the School of Interactive Computing and Senior Associate Dean in the College of Computing (CoC), at the Georgia Institute of Technology. Professor Essa works in the areas of Computer Vision, Artificial Intelligence, Machine Learning, Robotics, Computer Graphics, and Social Computing, with potential impact on Content Creation, Analysis and Production (e.g., Computational Photography & Video, Image-based Modeling and Rendering, etc.) Human Computer Interaction, Artificial Intelligence, Computational Behavioral/Social Sciences, and Computational Journalism research.He has published over 150 scholarly articles in leading journals and conference venues on these topics and several of his papers have also won best paper awards. He has been awarded the National Science Foundation CAREER Award and was elected an IEEE Fellow. He has held extended research consulting positions with Disney Research and Google Research and also was an Adjunct Faculty Member at Carnegie Mellon's Robotics Institute. He joined Georgia Tech in 1996 after his earning his Master's (1990), Ph.D. (1994), and holding a research faculty position at the Massachusetts Institute of Technology Media Lab (1988-1996).

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.

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. 

Ellen Zegura, Ph.D., is a Professor and the Stephen Fleming Chair in Telecommunications at the School of Computer Science, College of Computing at the Georgia Institute of Technology. Zegura’s research concerns the development of wide-area (Internet) networking services and mobile wireless networking.  Wide-area services are utilized by applications that are distributed across multiple administrative domains (e.g., web, file sharing, multi-media distribution). Her focus is on services implemented both at the network layer, as part of network infrastructure, and at the application layer.  In the context of mobile wireless networking, she is interested in challenged environments where traditional ad-hoc and infrastructure-based networking approaches fail. These environments have been termed Disruption Tolerant Networks.  She received a Bachelor's in Computer Science (1987) and Bachelor's in Electrical Engineering (1987), a Master's in Computer Science (1990) and the D.Sc. in Computer Science (1993) all from Washington University, St. Louis, Missouri. Since 1993, she has been a faculty member at Georgia Tech. She was an Assistant Dean in charge of Space and Facilities Planning from Fall 2000 to January 2003. She served as Interim Dean of the College for six months in 2002. She was Associate Dean responsible for Research and Graduate Programs from 2003-2005, and served as the first Chair of the School of Computer Science from 2005-2012.  Zegura is a Fellow of the IEEE and ACM.

Gil Weinberg is a professor and the founding director of Georgia Tech Center for Music Technology, where he leads the Robotic Musicianship group. His research focuses on developing artificial creativity and musical expression for robots and augmented humans. Among his projects are a marimba playing robotic musician called Shimon that uses machine learning for Jazz improvisation, and a prosthetic robotic arm for amputees that restores and enhances human drumming abilities. Weinberg presented his work worldwide in venues such as The Kennedy Center, The World Economic Forum, Ars Electronica, Smithsonian Cooper-Hewitt Museum, SIGGRAPH, TED-Ed, DLD and others. His music was performed with Orchestras such as Deutsches Symphonie-Orchester Berlin, the National Irish Symphony Orchestra, and the Scottish BBC Symphony while his research has been disseminated through numerous journal articles and patents. Dr. Weinberg received his MS and Ph.D. degrees in Media Arts and Sciences from MIT and his BA from the interdisciplinary program for fostering excellence in Tel Aviv University.

Aarn Stebner works at the intersection of manufacturing, machine learning, materials, and mechanics. He joined the Georgia Tech faculty as an associate professor of Mechanical Engineering and Materials Science and Engineering in 2020.

Previously, he was the Rowlinson Associate Professor of Mechanical Engineering and Materials Science at the Colorado School of Mines (2013 – 2020), a postdoctoral scholar at the Graduate Aerospace Laboratories of the California Institute of Technology (2012 – 2013), a Lecturer in the Segal Design Institute at Northwestern University (2009 – 2012), a Research Scientist at Telezygology Inc. establishing manufacturing and “internet of things” technologies for shape memory alloy-secured latching devices (2008-2009), a Research Fellow at the NASA Glenn Research Center developing smart materials technologies for morphing aircraft structures (2006 – 2008), and a Mechanical Engineer at the Electric Device Corporation in Canfield, OH developing manufacturing and automation technologies for the circuit breaker industry (1995 – 2000).

Wang's research is in the areas of design, manufacturing, and Integrated computational materials engineering. He is interested in computer-aided design, geometric modeling and processing, computer-aided manufacturing, multiscale simulation, and uncertainty quantification.

Currently, Wang studies integrated product-materials design and manufacturing process design, where process-structure-property relationships are established with physics-based data-driven approaches for design optimization. The Multiscale Systems Engineering research group led by him develops new methodologies and computational schemes to solve the technical challenges of high dimensionality, high complexity, and uncertainty associated with product, process, and systems design at multiple length and time scales.

Computational design tools for multiscale systems with sizes ranging from nanometers to kilometers will be indispensable for engineers' daily work in the near future. The research mission of the Multiscale Systems Engineering group is to create new modeling and simulation mechanisms and tools with underlying scientific rigor that are suitable for multiscale systems engineering for better and faster product innovation. Our education mission is to train engineers of the future to gain necessary knowledge as well as analytical, computational, communication, and self-learning skills for future work in a collaborative environment as knowledge creators and integrators. 

Dr. Medford is interested in leveraging materials informatics, statistics, and machine learning to maximize the practical impact of fundamental atomic-scale simulations in the field of surface science and catalysis. His research areas include heterogeneous catalysis, oxide surface chemistry, density functional theory, kinetic models, uncertainty quantification, and Bayesian optimization and inference.

Victor Fung is an Assistant Professor in the School of Computational Science and Engineering. Prior to this position, he was a Wigner Fellow and a member of the Nanomaterials Theory Insitute in the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory. A physical chemist by training, Fung now works at the intersection of scientific artificial intelligence, computing, and materials science/chemistry.