Benjamin Joffe is a Research Scientist in the Aerospace, Transportation & Advanced Systems Laboratory at the Georgia Tech Research Institute. He holds an M.S. in Computer Science from Georgia Tech. His work is at the intersection of Computer Vision, Machine Learning, and Robotics. His research interests include 3D Perception for highly-variable and deformable objects; robot learning for manipulation tasks; real-world generalization from synthetic and multi-modal data; Machine Learning for chemical sensing and biomanufacturing; Deep Learning algorithms for novel modalities and low-data scenarios. 

Maegan received her Ph.D. in Mechanical Engineering (ME) from the California Institute of Technology (Caltech) in May 2023. Prior, she also received a M.S. in ME from Caltech in 2019 and a B.S. in ME from Georgia Tech in 2017. After graduating with her Ph.D., Maegan conducted a brief postdoc at Caltech (May–August 2023), followed by a brief research position at Disney Research (September–December 2023). Generally speaking, her research interests lie at the intersection of control theory and human-robot interaction, with specific applications towards lower-limb assistive devices. Much of her research is centered around the question: “What is the right way to walk?”. In her free time, Maegan enjoys puzzles, playing video games, and the piano.

Maegan Tucker joined Georgia Tech as an assistant professor with joint appointments in the School of Electrical & Computer Engineering and the School of Mechanical Engineering in January 2024.

Dr. Lonnie Parker is the Collaborative Autonomy Branch Chief in the Robotics and Autonomous Systems Division of the ATAS Laboratory at GTRI and serves as the PI for multiple programs. He has 10+ years of experience in managing DoD-sponsored projects and is focused on designing collaborative behaviors for unmanned systems in both the maritime and air domains. Prior to joining GTRI, Dr. Parker spent seven years at a NAVSEA warfare center, NUWC Division Newport, where he performed research into maritime autonomy through ONR-sponsored and internally funded efforts. Lonnie received a Ph.D. in Electrical & Computer Engineering from Georgia Tech in 2012. His research advisor was Prof. Ayanna M. Howard. Lonnie received an M.S. and B.S. in Electrical Engineering from the Rochester Institute of Technology in 2006.

Lu Gan joined the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology as an Assistant Professor in January 2024. She leads the Lu's Navigation and Autonomous Robotics (Lunar) Lab at Georgia Tech, and is on the core faculty of the Institute for Robotics and Intelligent Machines. Her research interests include robot perception, robot learning, and autonomous navigation. Her group explores the use of computer vision, machine learning, estimation, probabilistic inference, kinematics and dynamics to develop autonomous systems in ground, air, and space applications.

She holds a B.S. in Automation from the University of Electronic Science and Technology of China, an M.S. in Control Engineering from Beihang University, and received her M.S. and Ph.D. in Robotics from the University of Michigan, Ann Arbor. Before joining Georgia Tech, she had a two-year appointment as a Postdoctoral Scholar at the Graduate Aerospace Laboratories of the California Institute of Technology and the Center for Autonomous Systems and Technologies at Caltech.

Larry P. Heck is a Professor with a joint appointment in the Schools of Electrical and Computer Engineering and Interactive Computing at the Georgia Institute of Technology. He holds the Rhesa S. Farmer Distinguished Chair of Advanced Computing Concepts and is a Georgia Research Alliance Eminent Scholar. His received the BSEE from Texas Tech University (1986), and MSEE and PhD EE from the Georgia Institute of Technology (1989,1991). He is a Fellow of the IEEE, inducted into the Academy of Distinguished Engineering Alumni at Georgia Tech and received the Distinguished Engineer Award from the Texas Tech University. He was a Senior Research Engineer with SRI (1992-98), VP of R&D at Nuance (1998-2005), VP of Search and Advertising Sciences at Yahoo! (2005-2009), Chief Scientist of the Microsoft Speech products and Distinguished Engineer in Microsoft Research (2009-2014), Principal Scientist with Google Research (2014-2017), CEO of Viv Labs and SVP at Samsung (2017-2021).

Omobolanle Ogunseiju is an assistant professor in the School of Building Construction, at Georgia Tech. Omobolanle received her Ph.D. in Environmental Design and Planning, from the Department of Building Construction, at Virginia Tech.

Her research interests focus on advancing workforce development (safety, health, and well-being), and developing smart communities through the application of wearable robots and Artificial Intelligence (enabled by digital twin, cyber-physical systems, data sensing, and reality capture technologies). She is particularly interested in understanding and shaping the human–technological dynamics involved in workforce development, safety, and health, especially within the construction sector. This includes understanding the ethical concerns of automation and robotics in the construction industry.

Omobolanle is an active member of the Diversity and Inclusion Council at the College of Design. During her Ph.D. studies, Omobolanle was recognized as the outstanding doctoral candidate at the Myers Lawson school of construction, and the outstanding doctoral student in the College of Architecture and Urban Studies at Virginia Tech.

She believes that the next generation of construction engineers should be trained to serve as innovators, risk managers, and leaders that shape public policy. As such, Omobolanle believes that teaching should be based on promoting experiential learning amongst students, applying a variety of engagement techniques, and providing hierarchical learning assessments. Omobolanle developed and teaches Construction Cost Management at the School of Building Construction, Georgia Tech, and will teach and develop Construction Technology courses in the coming semesters. She had the opportunity to teach course sections and conduct laboratories in Smart Construction, Building Systems Technology, and Wireless Sensing in Construction Management as a graduate teaching assistant at Virginia Tech.

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.