Chen Zhou is the associate chair for undergraduate studies and associate professor in the Stewart School of Industrial and Systems Engineering at Georgia Tech.. Dr. Zhou's research focus includes sustainable supply chain, distribution system design and manufacturing systems. Dr. Chen is a member of the Institute of Industrial Engineers, Society of Manufacturing Engineers and American Society of Engineering Education. Dr. Zhou received a B.S. degree from Tianjin University (China) in 1982, an M.S. in mechanical engineering from Pennsylvania State University in 1984, and a Ph.D. in industrial engineering from Pennsylvania State University in 1988.

Dr. Ye Zhao started as an Assistant Professor at the George W. Woodruff School of Mechanical Engineering in January 2019. Previously he was a Postdoctoral Fellow at Harvard University and obtained his Ph.D. from UT Austin, where he worked on robust motion planning and decision-making for robot manipulation and locomotion problems with frictional contact behaviors. At Georgia Tech, he directs the Laboratory for Intelligent Decision and Autonomous Robots. His research interests lie broadly in planning, control, decision-making, and learning algorithms of highly agile, contact-rich, and human-cooperative robots. Dr. Zhao is especially interested in computationally efficient optimization algorithms and formal methods for challenging robotics problems with formal guarantees on robustness, safety, autonomy, and real-time performance. The LIDAR group aims at pushing the boundary of robot autonomy, intelligent decision, robust motion planning, and symbolic planning. The long-term goal is to devise theoretical and algorithmic underpinnings for collaborative humanoid and mobile robots operating in unstructured and unpredictable environments while working alongside humans. Robotic applications primarily focus on agile bipedal and quadrupedal locomotion, manipulation, heterogeneous robot teaming, and mobile platforms for extreme environment maneuvering.

Dr. Fan Zhang received her Ph.D. in Nuclear Engineering and M.S. in Statistics from UTK in 2019. She is the recipient of the 2021 Ted Quinn Early Career Award from the American Nuclear Society and joined the Woodruff School in July, 2021. She is actively involved with multiple international collaborations on improving nuclear cybersecurity through the International Atomic Energy Agency (IAEA) and the DOE Office of International Nuclear Security (INS). Dr. Zhang’s research primarily focuses on the cybersecurity of nuclear facilities, online monitoring & fault detection using data analytics methods, instrumentation & control, and nuclear systems modeling & simulation. She has developed multiple testbeds using both simulators and physical components to investigate different aspects of cybersecurity as well as process health management.

Alenka Zajic is currently the Ken Byers Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. She has received the B.Sc. and M.Sc. degrees from the University of Belgrade, Belgrade, Serbia, in 2001 and 2003, respectively, and the Ph.D. degree in electrical and computer engineering from the Georgia Institute of Technology, Atlanta, in 2008. Before joining Georgia Tech as an assistant professor, Zajic was a post-doctoral fellow in the Naval Research Laboratory and visiting faculty in the School of Computer Science at the Georgia Institute of Technology. Zajic is the recipient of the following awards: IEEE Atlanta Section Outstanding Engineer Award (2019), The Best Poster Award at the IEEE International Conference on RFID (2018), NSF CAREER Award (2017), Best Paper Award at the 49th Annual IEEE/ACM International Symposium on Microarchitecture (2016), the Best Student Paper Award at the IEEE International Conference on Communications and Electronics (2014), Neal Shepherd Memorial Best Propagation Paper Award (2012), the Best Paper Award at the International Conference on Telecommunications (2008), the Best Student Paper Award at the Wireless Communications and Networking Conference (2007), IEEE Outstanding Chapter Award as a Chair of the Atlanta Chapter of the AP/MTT Societies (2016), LexisNexis Dean's Excellence Award (2016), and Richard M. Bass/Eta Kappa Nu Outstanding Teacher Award (2016). She was an editor for IEEE Transactions on Wireless Communications 2012-2017 and an executive editor for Wiley Transactions on Emerging Telecommunications Technologies 2011-2016 .

Aaron Young is an Associate Professor in Mechanical Engineering and is interested in designing and improving powered orthotic and prosthetic control systems for persons with stroke, neurological injury or amputation. His previous experience includes a post-doctoral fellowship at the University of Michigan in the Human Neuromechanics Lab working with exoskeletons and powered orthoses to augment human performance. He has also worked on the control of upper and lower limb prostheses at the Center for Bionic Medicine (CBM) at the Rehabilitation Institute of Chicago. His master's work at CBM focused on the use of pattern recognition systems using myoelectric (EMG) signals to control upper limb prostheses. His dissertation work at CBM focused on sensory fusion of mechanical and EMG signals to enable an intent recognition system for powered lower limb prostheses for use by persons with a transfemoral amputation.

Professor Yezzi was born in Gainsville, Florida and grew up in Minneapolis, Minnesota. He obtained both his Bachelor's degree and his Ph.D. in the Department of Electrical Engineering at the University of Minnesota with minors in mathematics and music. After completing his Ph.D., he continued his research as a post-Doctoral Research Associate at the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology in Boston, MA. His research interests fall broadly within the fields of image processing and computer vision. In particular he is interested in curve and surface evolution theory and partial differential equation techniques as they apply to topics within these fields (such as segmentation, image smoothing and enhancement, optical flow, stereo disparity, shape from shading, object recognition, and visual tracking). Much of Dr. Yezzi's work is particularly tailored to problems in medical imaging, including cardiac ultrasound, MRI, and CT. He joined the Georgia Tech faculty in the fall of 1999 where he has taught courses in DSP and is working to develop advanced courses in computer vision and medical image processing. Professor Yezzi consults with industry in the areas of visual inspection and medical imaging. His hobbies include classical guitar, opera, and martial arts.

W. Hong Yeo is a TEDx alumnus and biomechanical engineer. Since 2017, Yeo is an assistant professor of the George W. Woodruff School of Mechanical Engineering and Program Faculty in Bioengineering at the Georgia Institute of Technology. Before joining Georgia Tech, he has worked at Virginia Commonwealth University Medicine and Engineering as an assistant professor from 2014-2016. Yeo received his BS in mechanical engineering from INHA University, South Korea in 2003 and he received his Ph.D. in mechanical engineering and genome sciences at the University of Washington, Seattle in 2011. From 2011-2013, he worked as a postdoctoral research fellow at the Beckman Institute and Frederick Seitz Materials Research Laboratory at the University of Illinois at Urbana-Champaign. His research focuses on the fundamental and applied aspects of nanomechanics, biomolecular interactions, soft materials, and nano-microfabrication for nanoparticle biosensing and unusual electronic system development, with an emphasis on bio-interfaced translational nanoengineering. is an Editorial Board Member of Scientific Reports (Nature Publishing Group) and Scientific Pages of Bioengineering, and Review Editor of Frontiers of Materials (Frontiers Publishing Group). He serves as a technical committee member for IEEE Electronic Components and Technology Conference and Korea Technology Advisory Group at Korea Institute for Advancement of Technology. He has published more than 40 peer-reviewed journal articles, and has three issued and more than five pending patents. His research has been funded by MEDARVA Foundation, Thomas F. and Kate Miller Jeffress Memorial Trust, CooperVision, Inc., Korea Institute of Materials Science, Commonwealth Research Commercialization, and State Council of Virginia. Yeo is a recipient of a number of awards, including BMES Innovation and Career Development Award, Virginia Commercialization Award, Blavatnik Award Nominee, NSF Summer Institute Fellowship, Notable Korean Scientist Awards, and Best Paper/Poster Awards at ASME conferences.

Dr. Danfei Xu is an Assistant Professor in the School of Interactive Computing at Georgia Tech. Dr. Xu received a B.S. in Computer Science from Columbia University in 2015 and a Ph.D. in Computer Science from Stanford University in 2021. His research goal is to enable physical autonomy in everyday human environments with minimum expert intervention. Towards this goal, his work draws equally from Robotics, Machine Learning, and Computer Vision, including topics such as imitation & reinforcement learning, representation learning, manipulation, and human-robot interaction. His current research focuses on visuomotor skill learning, structured world models for long-horizon planning, and data-driven approaches to human-robot collaboration.

Anqi Wu is an Assistant Professor at the School of Computational Science and Engineering (CSE), Georgia Institute of Technology. She was a Postdoctoral Research Fellow at the Center for Theoretical Neuroscience, the Zuckerman Mind Brain Behavior Institute, Columbia University. She received her Ph.D. degree in Computational and Quantitative Neuroscience and a graduate certificate in Statistics and Machine Learning from Princeton University. Anqi was selected for the 2018 MIT Rising Star in EECS, 2022 DARPA Riser, and 2023 Alfred P. Sloan Fellow. Her research interest is to develop scientifically-motivated Bayesian statistical models to characterize structure in neural data and behavior data in the interdisciplinary field of machine learning and computational neuroscience. She has a general interest in building data-driven models to promote both animal and human studies in the system and cognitive neuroscience.

Michael (Mick) West joined ECE from the Georgia Tech Research Institute (GTRI) in 2022. He received his Ph.D. in electrical engineering from the University of Hawaii (UH) in 2006 and has over 28 years of professional experience with over 40 refereed journals and conference papers. 

West specializes in the development unmanned systems in extreme environments (under-ice, planetary, deep ocean, polar). He has been an invited speaker for United States Congressional leaders and their staff and top military personnel in the development of roadmaps for advancing current robotics research. He has served as PI on several Unmanned Systems programs developing novel enabling technologies including advanced control and power systems on underwater, ground, air and space platforms. West developed the first-of-its-kind under-ice vehicle, Icefin, in order to gather information about the changing polar ice and provide insight into areas of climate science, as well as biology and planetary science. The vehicle has been deployed over five seasons through the Ross Ice Shelf in Antarctica and provided never before seen images and scientific data of the Antarctic seafloor.