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.

Wei Xu is an associate professor in the School of Interactive Computing at the Georgia Institute of Technology. Xu received her Ph.D. in Computer Science from New York University, and her B.S. and M.S. from Tsinghua University. Her research interests are in natural language processing, machine learning, and social media. Her recent work focuses on text generation, stylistics, information extraction, robustness and controllability of machine learning models, and reading and writing assistive technology. She is a recipient of the NSF CAREER Award, CrowdFlower AI for Everyone Award, Criteo Faculty Research Award, and Best Paper Award at COLING'18. She has also received funds from DARPA and IARPA and is part of the Machine Learning Center and NSF AI CARING Institute at Georgia Tech.

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.

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. 

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. 

Anne Sullivan is an Assistant Professor in Digital Media and head of the StoryCraft Lab at Georgia Tech.

She received her PhD in Computer Science from University of California, Santa Cruz, where she created an artificial intelligence framework to support playable stories - stories that adapted and changed based on player choice. Before returning to school for her PhD, she was a game developer and designer with experience at AAA studios and as an independent developer.

Her research focuses on playful and storied interactive experiences from a feminist and humanistic perspective, with an emphasis on human-centered artificial intelligence (AI). To that end, Dr. Sullivan has established herself in the fields of critical game analysis through her work in feminist analysis of games, and co-creative AI through her work in educational interactive experiences and AI-assisted tools for craft and narratives. She also studies craft as an analog counterpart to playful and storied interactive experiences, researching in the exciting and emerging field of computational craft.

Dr. Sullivan is an award-winning quilter and the concept designer and producer of Loominary – a digital game system controlled with a loom - which has been shown internationally, including at the SAAM Arcade exhibit at the Smithsonian American Art Museum.

Education:

• PhD Computer Science - University of California, Santa Cruz

Areas of
Expertise:

• Computational Craft
• Craft
• Craft Games
• Digital Media
• Games
• Interactive Narrative
• Narrative
• STEM Education

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).

Dr. Jianjun Shi is the Carolyn J. Stewart Chair and Professor in H. Milton Stewart School of Industrial and Systems Engineering, with joint appointment in the George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology. Prior to joining Georgia Tech in 2008, he was the G. Lawton and Louise G. Johnson Professor of Engineering at the University of Michigan. He received his B.S. and M.S. in Electrical Engineering from the Beijing Institute of Technology in 1984 and 1987, and his Ph.D. in Mechanical Engineering from the University of Michigan in 1992. Dr. Shi is a pioneer in the development and application of data fusion for quality improvements. His methodologies integrate system informatics, advanced statistics, and control theory for the design and operational improvements of manufacturing and service systems by fusing engineering systems models with data science methods. He has produced 40 Ph.D. graduates, 27 of which have joined IE department as faculty members. Among them, 7 have received NSF CAREER Awards and one has received the NSF PECASE award. He has published one book and more than 180 papers. He has served as PI and co-PI for projects totaling more than 25 million dollars, which were funded by National Science Foundation, NIST Advanced Technology Program, Department of Energy, General Motors, Daimler-Chrysler, Ford, Boeing, Lockheed-Martin, Honeywell, Pfizer, Samsung, and various other industrial companies and funding agencies. The technologies developed in Dr. Shi’s research group have been widely implemented in various production systems with significant economic impacts. 

Dr. Shi is the founding chair of the Quality, Statistics and Reliability (QSR) Subdivision at the Institute for Operations Research and Management Science (INFORMS). He has served as the Editor-in-Chief of the IISE Transactions (2017-2020), the flagship journal of the Institute of Industrial and Systems Engineers. He also served as the Focus Issue Editor of IISE Transactions on Quality and Reliability Engineering (2007-2017), editor of Journal of System Science and Complexity, and advisory editor of Journal of Quality Technology and Quantitative Management (QTQM). He is a Fellow of American Society of Mechanical Engineering (ASME), a Fellow of the Institute of Industrial and Systems Engineering (IISE), a Fellow of Institute of Operations Research and the Management Science (INFORMS), a Fellow of Society of Manufacturing Engineering (SME), an Academician of the International Academy for Quality, and a member of National Academy of Engineering (NAE) of the USA. 

Dr. Shi received various awards for his research and teaching, including the George Box Medal (2022), ASQ Walter Shewhart Medal (2021), The S. M. Wu Research Implementation Award (2021), ASQ Brumbaugh Award (2019), The Horace Pops Medal Award (2018), IISE David F. Baker Distinguished Research Award (2016), the IIE Albert G. Holzman Distinguished Educator Award (2011), Forging Achievement Award from Forging Industry Educational and Research Foundation (2007), Monroe-Brown Foundation Research Excellence Award (2007), the 1938E Award (1998) at The University of Michigan, and NSF CAREER Award (1996).

Rahul Saxena is the Interim Director for CREATE-X and the Associate Director for LAUNCH. Leading up to this role, Saxena had a career as a Venture Capitalist, startup CEO, entrepreneur, mechatronic design engineer, and published academic researcher. Saxena is a mechanical engineering Georgia Tech alumnus, earned his European Master’s degree in Fluid Mechanics from the Von Karman Institute for Fluid Dynamics, and earned his MBA from Emory University. Saxena worked for Seraph Group, a venture capital firm, for 10 years evaluating and investing in companies while also holding the role of CEO in a company and serving on several boards of companies that went on to be acquired. 

Saleeby was formerly a research staff member from Oak Ridge National Laboratory where he was in the Manufacturing Science Division. His work focuses on connecting machines and manufacturing processes with Industry 4.0 and Industrial IoT technologies. Current interests center on applications of data analytics and closed-loop control for Hybrid Manufacturing processes, where additive and subtractive (machining) processes are combined within a single machine tool.