Shreyas Kousik is an assistant professor in the George W. Woodruff School of Mechanical Engineering. Previously, Shreyas was a postdoctoral scholar at Stanford University, working in the ASL under Prof. Marco. Kousik completed a postdoc with Prof. Grace Gao in the NAV Lab. He received his Ph.D. in Mechanical Engineering at the University of Michigan, advised by Prof. Ram Vasudevan in the ROAHM Lab and received his undergraduate degree in Mechanical Engineering at Georgia Tech, advised by Prof. Antonia Antoniou.

Kousik’s research is focused on guaranteeing safety in autonomy via collision avoidance methods for robots. His lab’s goal is to translate safety in math to safety on real robots by exploring ways to model uncertainty from autonomous perception and estimation systems and ensure that these models are practical for downstream planning and control tasks

Animesh Garg is a Stephen Fleming Early Career Assistant Professor at School of Interactive Computing at Georgia Tech. He leads the People, AI, and Robotics (PAIR) research group. He is on the core faculty in the Robotics and Machine Learning programs. Animesh is also a Senior Researcher at Nvidia Research. Animesh earned a Ph.D. from UC Berkeley and was a postdoc at the Stanford AI Lab. He is on leave from the department of Computer Science at University of Toronto and CIFAR Chair position at the Vector Institute.

Garg earned his M.S. in Computer Science and Ph.D. in Operations Research from UC, Berkeley. He worked with Ken Goldberg at Berkeley AI Research (BAIR). He also worked closely with Pieter Abbeel, Alper Atamturk & UCSF Radiation Oncology. Animesh was later a postdoc at Stanford AI Lab with Fei-Fei Li and Silvio Savarese.

Garg's research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments. His group focuses on understanding structured inductive biases and causality on a quest for general-purpose embodied intelligence that learns from imprecise information and achieves flexibility & efficiency of human reasoning.

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.

Alex Abramson is an assistant professor in the School of Chemical and Biomolecular Engineering at Georgia Tech. His research, which focuses on drug delivery and bioelectronic therapeutics, has been featured in news outlets such as The New York Times, NPR, and Wired. Abramson has received several recognitions for scientific innovation, including being named a member of the Forbes 30 Under 30 Science List and the MIT Technology Review Innovators Under 35 List. He is passionate about translating scientific endeavors from bench to bedside. Large pharmaceutical companies have exclusively licensed a portfolio of his patents to bring into clinical trials, and Abramson serves as a scientific advisor overseeing their commercialization. In addition to his scientific endeavors, Abramson plays an active role in his community by leading diversity and inclusion efforts on campus and volunteering as a STEM tutor to local students.

Abramson received a B.S. in chemical and biomolecular engineering from Johns Hopkins University and a Ph.D. in chemical engineering from MIT as an NSF Graduate Research Fellow under the direction of Professors Robert Langer and Giovanni Traverso. He conducted postdoctoral work at Stanford University as an NIH fellow with Professors Zhenan Bao and the late Sanjiv S. Gambhir.

The Abramson Lab develops ingestible, implantable, and wearable robotic therapeutic devices that solve key healthcare problems and provide measurable therapeutic outcomes. Our translationally focused research spans a multitude of areas, including (1) drug delivery devices for optimal drug adherence, (2) soft materials for bioelectronic sensors and therapeutics, and (3) preclinical drug screening technologies.

Stuart Michelson is a member of the research faculty at the Georgia Tech Research Institute and is known as a subject matter expert in Human Systems Engineering. He leads Human Factors and Ergonomics and Human Systems Integration (HSI) efforts for DoD customers specializing in tactical display design spanning command and control, training, unmanned vehicle ground control stations, Manned-unmanned teaming, and mission planning. He has expertise in digital human modeling/ergonomic/anthropometric analyses to assess cockpit accommodation and experience with wearable soldier systems and tactical equipment design.

Since 2000, Michelson has organized the American venue and annual Symposium on Dynamic Flight Behavior for Aerial Robotics for the International Aerial Robotics Competition (IARC), the longest running collegiate aerial challenge in the world focused on advancing the state of the art in aerial robotic behavior.

Michelson has held an Associate Human Factors Professional status from the Board of Certification in Professional Ergonomics, is recognized as a graphic design professional by the International Academy of Computer Training, and is certified to conduct ethical Human Subjects Research.

Michelson has supported and led numerous programs within the Georgia Tech Research Institute leveraging his knowledge of soldier loadout and autonomous unmanned systems. Notably, he has designed graphical user interfaces, developed human-centered system requirements, led programs to quantify human performance, assessed anthropometric accommodations, and supported system test and evaluation for DoD stakeholders spanning the United States Navy, Air Force, Army, and Marine Corps.

Jun Ueda received his B.S., M.S., and Ph.D. degrees from Kyoto University, Japan, in 1994, 1996, and 2002 all in Mechanical Engineering. From 1996 to 2000, he was a Research Engineer at the Advanced Technology Research and Development Center, Mitsubishi Electric Corporation, Japan. He was an Assistant Professor of Nara Institute of Science and Technology, Japan, from 2002 to 2008. During 2005-2008, he was a visiting scholar and lecturer in the Department of Mechanical Engineering, Massachusetts Institute of Technology. He joined the G. W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technology as an Assistant Professor in 2008 where he is currently a Professor. He received Fanuc FA Robot Foundation Best Paper Award in 2005, IEEE Robotics and Automation Society Early Academic Career Award in 2009, Advanced Robotics Best Paper Award in 2015, and Nagamori Award in 2021. 

Yue Chen is an assistant professor in the Department of Biomedical Engineering, GT/Emory. He received his Ph.D. degree in Mechanical Engineering from Vanderbilt University, M.S. in Mechanical Engineering from Hong Kong Polytechnic University, and a B.S. in Vehicle Engineering from Hunan University. His research focused on designing, modeling, and control of continuum robots and apply them in medicine.

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.

Prof. Pradalier is Associate Professor at GeorgiaTech Lorraine, the French campus of the Georgia Institute of Technology (a.k.a. GeorgiaTech) since September 2012. He defended his “Habilitation à Diriger des Recherches” (Authority to Supervise Research) in 2015 on the topic of “Autonomous Mobile Systems for Long-Term Operations in Spatio-Temporal Environments” at the National Polytechnic Institute of Toulouse (INPT). 

His objective is to extend the activity of the CNRS IRL2958 GT-CNRS towards robotics, leveraging on one side the strong robotic research inside CNRS and on the other side the collaboration potential with the Robotics and Intelligent Machines (RIM) laboratory at GTL. 

At the IRL, he is now the coordinator of the H2020 BugWright2 project, has been involved in H2020 project Flourish and PF7 project Noptilus, as well as in projects on environmental monitoring. 

From November 2007 until December 2012, Dr. Pradalier has been deputy director in the Autonomous Systems Lab at ETH Zürich. In this role, he was the technical coordinator of the V-Charge project (IP, 2010-2014) and also involved in the development of innovative robotic platforms such as autonomous boats for environment monitoring or prototype space rovers funded by the European Space Agency. He is a founding member of the ETH start-up Skybotix, within which he was responsible for software development and integration. 

From 2004 to 2007, Dr. Pradalier was a research scientist at CSIRO Australia. He was then involved in the development of software for autonomous large industrial robots and an autonomous underwater vehicle for the monitoring of the Great Barrier Reef, Australia. 

He received his Ph.D. in 2004 from the National Polytechnic Institute of Grenoble (INPG) on the topic of autonomous navigation of a small urban mobility system and he is Ingénieur from the National Engineering School for Computer Science and Applied Math in Grenoble (ENSIMAG).

Eric Feron is a professor of Electrical, Computer, and Mechanical Engineering. He is the director of the Robotics, Intelligent Systems, and Control (RISC) Laboratory. He recently joined the KAUST CEMSE Division from the Georgia Institute of Technology. Prior to his time at Georgia Tech, he was an active faculty member in MIT's Aeronautics and Astronautics department from 1993 until 2005. Feron’s career in academia began in Paris, France, where he obtained his B.S. and M.S. from École Polytechnique and École Normale Superieure, respectively. He later completed his Ph.D. in aerospace engineering at Stanford University, U.S. 

Feron's research interests center around the use of elementary concepts of control systems, optimization and computer science to address key issues in modern robotic systems. More specifically, aerobatic control of uncrewed aerial vehicles, multi-agent operations, including air traffic control systems and safety-critical software system certification. Feron is also interested in geometric control systems and control theory in general. Among his latest projects, there are a fractal drone, a few positioning systems, a wheel nature could have invented, and a self-reproducing 3D printer. 

Feron has always taught at least one course per semester since the onset of his academic career. Feron believes teaching offers a fantastic outlet to communicate display his past research and inspire his new research projects with the thoughts of his classroom students. He has taught subjects as diverse as cyber-physical systems, control systems, operations research, linear programming, software engineering, and flight mechanics. Feron is a strong proponent and author of quality online education products. He also believes in communicating knowledge through all available mechanisms, including analytical and experimental, acknowledging the multiple learning modalities preferred by students, undergraduate and graduate.