Nick Sahinidis is the Butler Family Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering and the School of Chemical and Biomolecular Engineering at Georgia Tech. His current research activities are at the interface between computer science and operations research, with applications in various engineering and scientific areas, including: global optimization of mixed-integer nonlinear programs: theory, algorithms, and software; informatics problems in chemistry and biology; process and energy systems engineering. Sahinidis has served on the editorial boards of many leading journals and in various positions within AIChE (American Institute of Chemical Engineers). He has also served on numerous positions within INFORMS (Institute for Operations Research and the Management Sciences), including Chair of the INFORMS Optimization Society. He received an NSF CAREER award, the INFORMS Computing Society Prize, the MOS Beale-Orchard-Hays Prize, the Computing in Chemical Engineering Award, the Constantin Carathéodory Prize, and the National Award and Gold Medal from the Hellenic Operational Research Society. Sahinidis is a member of the U.S. National Academy of Engineering and a fellow of AIChE and INFORMS.

Thomas Ploetz is a computer scientist with expertise and almost 15 years of experience in Pattern Recognition and Machine Learning research (Ph.D. from Bielefeld University, Germany). His research agenda focuses on applied machine learning that is developing systems and innovative sensor data analysis methods for real world applications. Primary application domain for his work is computational behavior analysis, in which he develops methods for automated and objective behavior assessments in naturalistic environments. Main driving functions for his work are "in the wild" deployments and the development of systems and methods that have a real impact on people’s lives.

In 2017, Dr. Ploetz joined the School of Interactive Computing at the Georgia Institute of Technology, where he works as an associate professor. Prior to this, he was an academic at the School of Computing Science at Newcastle University in Newcastle in Tyne, U.K., where he was a reader (associate professor) for Computational Behavior Analysis affiliated with Open Lab, Newcastle's interdisciplinary center for research in digital technologies.

Visit the Computational Behavior Analysis Lab: cba.gatech.edu.

Our work centers on understanding how the brain represents information and intention, and using this knowledge to develop high-performance, robust, and practical assistive devices for people with disabilities and neurological disorders. We take a dynamical systems approach to characterizing the activity of large populations of neurons, combined with rigorous systems engineering (signal processing, machine learning, and real-time systems) to advance the performance of brain-machine interfaces and neuromodulatory devices.

Christopher J. MacLellan is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology, where he leads the Teachable AI Lab (TAIL; https://tail.cc.gatech.edu). His work on cognitive systems aims to advance our understanding of how people teach and learn and to build AI systems that can teach and learn like people do and in ways that are compatible with people. He explores the development of computational models of learning and how these models can support the development of AI technologies, such as intelligent tutoring systems and medical decision support systems, at scale.

He also investigates how data collected about how people learn and make decisions can be leveraged to drive the development of better cognitive models and computational learning systems. Chris has been a principal investigator on multiple sponsored project awards with DARPA, the U.S. Army, ONR, and NSF. He has also received external recognition for his work, such as the 2022 EAAI Now and Future AI Educator award as well as being named on the 2021 Technical.ly RealLIST of technologists building Philadelphia’s future.  

Prior to his position at Georgia Tech, Chris was an Assistant Professor of Information Science and Computer Science (by co-appointment) at Drexel University. Before that, he completed his PhD in Human-Computer Interaction at Carnegie Mellon University's School of Computing, where he was a fellow in the Program for Interdisciplinary Education Research (PIER).

The products of his work have immediate implications for AI-powered technology development. For example, through his work with the NSF-funded AI ALOE Institute, Chris is developing tools that let teachers build AI-powered tutors by naturally teaching an AI agent rather than programming. His work also has many broader implications, such as enabling doctors to support the development of AI-powered diagnoses tools where few training examples are available (DARPA-funded POCUS project) and for creating personal assistant agents that can engage in collaborative learning to support more effective human-machine teaming (ARL-funded STRONG project).

Research Areas: 

Artificial Intelligence; Cognitive Systems; Cognitive and Learning Sciences; Human-Computer Interaction; Learning Technology.

Dr. Liang began at Tech in 1990 as an assistant professor. Previously, he was an assistant professor at Oklahoma State University. He was named to the Bryan Professorship in 2005. He was President of Walsin-Lihwa Corporation in 2008-2010.

Professor Kurfess began his academic career at Carnegie Mellon University where he rose to the rank of Associate Professor. In 1994, he moved to the Georgia Institute of Technology where he rose to the rank of Professor in the George W. Woodruff School of Mechanical Engineering. In 2005, he was named Professor and BMW Chair of Manufacturing in the Department of Mechanical Engineering at Clemson University’s International Center for Automotive Research. In 2012, he returned to Georgia Tech as a Professor of Mechanical Engineering and the HUSCO/Ramirez Distinguished Chair in Fluid Power and Motion Control.

During 2012-2013, Dr. Kurfess was on leave serving as the Assistant Director for Advanced Manufacturing at the Office of Science and Technology Policy in the Executive Office of the President of the United States of America. In this position he had responsibility for engaging the Federal sector and the greater scientific community to identify possible areas for policy actions related to manufacturing. He was responsible for coordinating Federal advanced manufacturing R&D, addressing issues related to technology commercialization, identifying gaps in current Federal R&D in advanced manufacturing, and developing strategies to address these gaps. During  2019-2021 he was on leave serving as the Chief Manufacturing Officer and the Founding Director for the Manufacturing Science Division at Oak Ridge National Laboratory, where he was responsible for strategic planning in advanced manufacturing.

Professor Kurfess has served as a special consultant of the United Nations to the Government of Malaysia in the area of applied mechatronics and manufacturing, and as a participating guest at the Lawrence Livermore National Laboratory in their Precision Engineering Program. He has testified in a number of patent cases, including testifying at the International Trade Commission (ITC). He is currently the President of the American Society of Mechanical Engineers (ASME) and also serves on the Board of Governors of ASME. He is the CTO of the National Center for Manufacturing Sciences (NCMS) and serves on its Board of Directors. He also serves on the Board of Directors for the National Center for Defense Manufacturing and Machining (NCDMM), and on the Board of Trustees of the MT Connect Institute. He served on the Board of Directors for the Society of Manufacturing Engineers (SME) and was the President of SME in 2018. He is an appointed member of the Department of Energy, National Nuclear Security Administration, Advisory Committee for Nuclear Security, and an appointed member of the Department of the Navy Science and Technology Board.

His research focuses on the design and development of advanced systems targeting the automotive sector (OEM and supplier) including vehicle and production systems. He has significant experience in high precision manufacturing and metrology systems. He has received numerous awards including a National Science Foundation (NSF) Young Investigator Award, an NSF Presidential Faculty Fellowship Award, the ASME Pi Tau Sigma Award, SME Young Manufacturing Engineer of the Year Award, the ASME Blackall Machine Tool and Gage Award, the ASME Gustus L. Larson Award, an ASME Swanson Federal Award, and the SME Education Award. He is an elected member of the National Academy of Engineering, and a Fellow of the AAAS, the SME and the ASME.

Ruth Kanfer is a psychologist and professor at Georgia Institute of Technology in the area of Industrial and Organizational Psychology. She is best known for her research in the fields of motivation, goal setting, self-regulation, job search, adult learning, and future of work. Kanfer has received numerous awards for her research contributions including the American Psychological Association Distinguished Scientific Award for an Early Career Contribution in Applied Research in 1989, the Society for Industrial and Organizational Psychology (SIOP) William R. Owens Scholarly Achievement Award in 2006 and the SIOP Distinguished Scientific Contributions Award in 2007. Ruth Kanfer has authored influential papers on a variety of topics including the interaction of cognitive abilities and motivation on performance, the influence of personality and motivation on job search and employment, and a review chapter on motivation in an organizational setting.

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.