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.

May Dongmei Wang, Ph.D., is The Wallace H Coulter Distinguished Faculty Fellow, professor of BME, ECE and CSE, Director of Biomedical Big Data Initiative, and Georgia Distinguished Cancer Scholar. She is also Petit Institute Faculty Fellow, Kavli Fellow, Fellow of AIMBE, Fellow of IEEE, and Fellow of IAMBE. She received BEng from Tsinghua University China and MS/PhD from Georgia Institute of Technology (GIT). Dr. Wang’s research and teaching are in Biomedical Big Data and AI-Driven Biomedical Health Informatics and Intelligent Reality (IR) for predictive, personalized, and precision health. She has published over 270 referred journal and conference proceeding articles (13,500+ GS-Citations) and delivered over 280 invited and keynote lectures. Dr. Wang’s research has been supported by NIH, NSF, CDC, GRA, GCC, VA, Children’s Healthcare of Atlanta, Enduring Heart Foundation, Wallace Coulter Foundation, Carol Ann and David Flanagan Foundation, Shriner’s Hospitals, Microsoft Research, HP, UCB, and Amazon.

Dr. Wang chairs IEEE Engineering in Medicine and Biology Society (EMBS) BHI-Technical Community and ACM Special Interest Group in Bioinformatics (SIGBio), and is the Senior Editor of IEEE Journal of Biomedical & Health Informatics (IF=7.02), and Associate Editor for IEEE Transactions on BME, and IEEE Review of BME. She was IEEE EMBS Distinguished Lecturer and PNAS (Proceeding of National Academy of Sciences) Emerging Area Editor. During the past decade, Dr. Wang has been a standing panelist for NIH Study Sections, NSF Smart and Connect Health, and Brain Canada, and has co-chaired and helped organize more than 10 conferences by IEEE Engineering in Medicine and Biologics  Gordon Research Conferences, ACM Special Interest Groups in Bioinformatics, and IEEE Future Directions.

Dr. Wang received GIT Outstanding Faculty Mentor for Undergrad Research Award and Emory University MilliPub Award for a high-impact paper cited over 1,000 times. She was selected into 2022 Georgia Tech LeadingWomen Program and 2021 Georgia Tech Provost Emerging Leaders Program. Previously, she was Carol Ann and David Flanagan Distinguished Faculty Fellow, GIT Biomedical Informatics Program Co-Director in ACTSI, and Bioinformatics and Biocomputing Core Director in NIH/NCI-Sponsored U54 Center for Cancer Nanotechnology Excellence.

Kai Wang recently attained his Ph.D. in Computer Science at Harvard University where he was advised by Professor Milind Tambe. His research interests include multi-agent systems, computational game theory, machine learning and optimization, and their applications in public health and conservation. One of Wang's key technical contributions includes decision-focused learning, which integrates machine learning and optimization to strengthen learning performance; with his algorithms currently deployed assisting a non-profit in India focused on improving maternal and child health. He is the recipient of the Siebel Scholars award and the best paper runner-up award at AAAI 2021. 

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. 

Sherri joined the Business Analytics Center at Scheller College of Business in August 2017 as the Corporate Engagement Manager. She is responsible for identifying, developing and maintaining corporate partnerships that drive collaboration between the Business Analytics Center and the analytics industry. 

Before joining the Business Analytics Center, Sherri worked as a Corporate Relations Manager for the Georgia Tech Master of Science in Analytics Program. Prior to joining Georgia Tech, she built a 25+ year accomplished track record in business development, corporate relations, program management and fund raising. Her extensive experience spans multiple industry sectors in Technology, Consumer Products, Education and Nonprofit.

Richard (Rich) Vuduc is an Associate Professor at the Georgia Institute of Technology (“Georgia Tech”), in the School of Computational Science and Engineering, a department devoted to the study of computer-based modeling and simulation of natural and engineered systems. His research lab, The HPC Garage (@hpcgarage), is interested in high-performance computing, with an emphasis on algorithms, performance analysis, and performance engineering. He is a recipient of a DARPA Computer Science Study Groupgrant; an NSF CAREER award; a collaborative Gordon Bell Prize in 2010; Lockheed-Martin Aeronautics Company Dean’s Award for Teaching Excellence (2013); and Best Paper Awards at the SIAM Conference on Data Mining (SDM, 2012) and the IEEE Parallel and Distributed Processing Symposium (IPDPS, 2015), among others. He has also served as his department’s Associate Chair and Director of its graduate programs. External to Georgia Tech, he currently serves as Chair of the SIAM Activity Group on Supercomputing (2018-2020); co-chaired the Technical Papers Program of the “Supercomputing” (SC) Conference in 2016; and serves as an associate editor of both the International Journal of High-Performance Computing Applications and IEEE Transactions on Parallel and Distributed Systems. He received his Ph.D. in Computer Science from the University of California, Berkeley, and was a postdoctoral scholar in the Center for Advanced Scientific Computing the Lawrence Livermore National Laboratory.

Santosh Vempala is a prominent computer scientist. He is a Distinguished Professor of Computer Science at the Georgia Institute of Technology. His main work has been in the area of Theoretical Computer Science. 

Vempala secured B.Tech. degree in Computer Science and Engineering from Indian Institute of Technology, Delhi, in 1992 then he attended Carnegie Mellon University, where he received his Ph.D. in 1997 under professor Avrim Blum. 

In 1997, he was awarded a Miller Fellowship at Berkeley. Subsequently, he was a professor at MIT in the Mathematics Department, until he moved to Georgia Tech in 2006. 

His main work has been in the area of theoretical computer science, with particular activity in the fields of algorithms, randomized algorithms, computational geometry, and computational learning theory, including the authorship of books on random projection and spectral methods. 

In 2008, he co-founded the Computing for Good (C4G) program at Georgia Tech.

Vempala has received numerous awards, including a Guggenheim Fellowship, Sloan Fellowship, and being listed in Georgia Trend's 40 under 40.[5] He was named Fellow of ACM "For contributions to algorithms for convex sets and probability distributions" in 2015.[6] He was named a Fellow of the American Mathematical Society, in the 2022 class of fellows, "for contributions to randomized algorithms, high-dimensional geometry, and numerical linear algebra, and service to the profession".

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.