Craig Tovey is a Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He also co-directs CBID, the Georgia Tech Center for Biologically Inspired Design. 

Dr. Tovey's principal research and teaching activities are in operations research and its interdisciplinary applications to social and natural systems, with emphasis on sustainability, the environment, and energy. His current research concerns inverse optimization for electric grid management, classical and biomimetic algorithms for robots and webhosting, the behavior of animal groups, sustainability measurement, and political polarization.  

Dr. Tovey received a Presidential Young Investigator Award in 1985 and the 1989 Jacob Wolfowitz Prize for research in heuristics. He was granted a Senior Research Associateship from the National Research Council in 1990, was named an Institute Fellow at Georgia Tech in 1994, and received the Class of 1934 Outstanding Interdisciplinary Activity Award in 2011. In 2016, Dr. Tovey was recognized by the ACM Special Interest Group on Electronic Commerce with the Test of Time Award for his work as co-author of the paper “How Hard Is It to Control an Election?” He was a 2016 Golden Goose Award recipient for his role on an interdisciplinary team that studied honey bee foraging behavior which led to the development of the Honey Bee Algorithm to allocate shared webservers to internet traffic. 

Dr. Tovey received an A.B. in applied mathematics from Harvard College in 1977 and both an M.S. in computer science and a Ph.D. in operations research from Stanford University in 1981. 

Evangelos Theodorou earned his Diploma in Electronic and Computer Engineering from the Technical University of Crete (TUC), Greece in 2001. He has also received a MSc in Production Engineering from TUC in 2003, a MSc in Computer Science and Engineering from University of Minnesota in spring of 2007 and a MSc in Electrical Engineering on dynamics and controls from the University of Southern California(USC) in Spring 2010. In May of 2011 he graduated with his Ph.D., in Computer Science at USC. After his Ph.D., he became a Postdoctoral Research Associate with the department of Computer Science and Engineering, University of Washington, Seattle. In July 2013 he joined the faculty of the school of Aerospace Engineering at Georgia Institute of Technology as Assistant Professor. His theoretical research spans the areas of control theory, machine learning, information theory and statistical physics. Applications involve autonomous planning and control in robotics and aerospace systems, bio-inspired control and design.

During his graduate work at UC, Berkeley, Simon sought to uncover general principles of animal locomotion that reveal control strategies underlying the remarkable stability and maneuverability of movement in nature. His work has demonstrated the importance animals’ natural dynamics for maintaining stability in the absence of neural feedback. His research emphasizes the importance of placing neural control in the appropriate dynamical context using mathematical and physical models. He has collaborated with researchers at four other institutions to transfer these principles to the design of the next generation of bio-inspired legged robots. 

Simon received his Ph.D. in Integrative Biology at UC, Berkeley and has been a Hertz Fellow since 2002. His work has led to fellowships and awards from the National Science Foundation, the University of California, the Woods Hole Marine Biological Institute, the American Physical Society, the Society of Integrative and Comparative Biology, and the International Association of Physics Students. He is also currently affiliated the new Center for Interdisciplinary Bio-Inspiration in Education and Research (CIBER) at Berkeley.

Dr. Gregory S. Sawicki is the Interim Executive Director of the Institute for Robotics and Intelligent Machines and Professor and Joseph Anderer Faculty Fellow at Georgia Tech with appointments in the George W. Woodruff School of Mechanical Engineering and the School of Biological Sciences. He holds a B.S. from Cornell University ('99) and a M.S. in Mechanical Engineering from University of California-Davis ('01). Dr. Sawicki completed his Ph.D. in Human Neuromechanics at the University of Michigan, Ann-Arbor ('07) and was an NIH-funded Post-Doctoral Fellow in Integrative Biology at Brown University ('07-'09). Dr. Sawicki was a faculty member in the Joint Department of Biomedical Engineering at NC State and UNC Chapel Hill from 2009-2017. In summer of 2017, he joined the faculty at Georgia Tech with appointments in Mechanical Engineering 3/4 and Biological Sciences 1/4.

Tom Sammon focuses on implementing lean manufacturing practices and helping companies develop capital equipment applications.

Dr. Sadegh's early research work was in the field of robotics and automation. His major contribution to this field was the development of a class of adaptive and learning controllers for nonlinear mechanical systems including robotic manipulators. This work, which evolved from his doctoral research, enables a robot to learn a repetitive task through practice, much like a human being, and without requiring a precise model. He later demonstrated that implementing this learning controller can significantly improve the performance of industrial robots without significantly increasing their cost or complexity, and has the potential to improve the accuracy, autonomy, and productivity of automated manufacturing systems. In addition to robotics, he developed a similar learning controller for speed regulation of copier photoreceptors as part of a project sponsored by the Xerox Corporation. Dr. Sadegh began at Tech in 1988 as an Assistant Professor.

Jonathan Rogers joined the Georgia Tech faculty in Fall 2013 as an Assistant Professor of Mechanical Engineering. Prior to joining Georgia Tech, he was an Assistant Professor of Aerospace Engineering at Texas A&M University from 2011 to 2013.

Spyros Reveliotis is a professor in the Stewart School of Industrial & Systems Engineering at Georgia Tech. Dr. Reveliotis' research interests are primarily in discrete event systems theory and its applications, especially in the control of flexibly automated workflows and the traffic management of multi-agent systems evolving over graphs. He also has an active interest in machine learning theory and its applications. Dr. Reveliotis is an IEEE Fellow, and a member of INFORMS. Dr. Reveliotis completed his Ph.D. studies in industrial engineering at the University of Illinois at Urbana-Champaign. He also holds a B.Sc. degree in Electrical Engineering from the National Technical University of Athens, Greece, and an M.Sc. degree in Computer Systems Engineering from Northeastern University.

Dr. Rehg's research interests include computer vision, computer graphics, machine learning, robotics, and distributed computing. He co-directs the Computational Perception Laboratory (CPL) and is affiliated with the GVU Center, Aware Home Research Institute, and the Center for Experimental Research in Computer Science. In past years he has taught "Computer Vision" (CS 4495/7495) and "Introduction to Probabilistic Graphical Models" (CS 8803). He is currently teaching "Pattern Recognition" (CS 4803) and "Computer Graphics" (CS 4451). Dr. Rehg received the 2005 Raytheon Faculty Fellowship Award from the College of Computing. His paper with Ph.D. student Yushi Jing and collaborator Vladimir Pavlovic was the recipient of a Distinguished Student Paper Award at the 2005 International Conference on Machine Learning. Dr. Rehg currently serves on the Editorial Board of the International Journal of Computer Vision. He was the Short Courses Chair for the International Conference on Computer Vision (ICCV) in 2005 and the Workshops Chair for ICCV 2003. Dr. Rehg consults for several companies and has served as an expert witness. His research is funded by the NSF, DARPA, Intel Research, Microsoft Research, and the Mitsubishi Electric Research Laboratories.

Note: Rehg recently moved to the University of Illinois Urbana-Champaign as the Founder Professor of Computer Science and Industrial and Enterprise Systems Engineering.