Dhruv Batra is an Associate Professor in the School of Interactive Computing at Georgia Tech. His research interests lie at the intersection of machine learning, computer vision, natural language processing, and AI, with a focus on developing intelligent systems that are able to concisely summarize their beliefs about the world with diverse predictions, integrate information and beliefs across different sub-components or `modules' of AI (vision, language, reasoning, dialog), and interpretable AI systems that provide explanations and justifications for why they believe what they believe. In past, he has also worked on topics such as interactive co-segmentation of large image collections, human body pose estIMaTion, action recognition, depth estIMaTion, and distributed optimization for inference and learning in probabilistic graphical models. He is a recipient of the Office of Naval Research (ONR) Young Investigator Program (YIP) award (2016), the National Science Foundation (NSF) CAREER award (2014), Army Research Office (ARO) Young Investigator Program (YIP) award (2014), Virginia Tech College of Engineering Outstanding New Assistant Professor award (2015), two Google Faculty Research Awards (2013, 2015), Amazon Academic Research award (2016), Carnegie Mellon Dean's Fellowship (2007), and several best paper awards (EMNLP 2017, ICML workshop on Visualization for Deep Learning 2016, ICCV workshop Object Understanding for Interaction 2016) and teaching commendations at Virginia Tech. His research is supported by NSF, ARO, ARL, ONR, DARPA, Amazon, Google, Microsoft, and NVIDIA. Research from his lab has been extensively covered in the media (with varying levels of accuracy) at CNN, BBC, CNBC, Bloomberg Business, The Boston Globe, MIT Technology Review, Newsweek, The Verge, New Scientist, and NPR. From 2013-2016, he was an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech, where he led the VT Machine Learning & Perception group and was a member of the Virginia Center for Autonomous Systems (VaCAS) and the VT Discovery Analytics Center (DAC). From 2010-2012, he was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC), a philanthropically endowed academic computer science institute located on the University of Chicago campus. He received his M.S. and Ph.D. degrees from Carnegie Mellon University in 2007 and 2010 respectively, advised by Tsuhan Chen. In past, he has held visiting positions at the Machine Learning Department at CMU, CSAIL MIT, Microsoft Research, and Facebook AI Research.

Stephen Balakirsky is the Chief Scientist for the Aerospace, Transportation & Advanced Systems Laboratory at the Georgia Tech Research Institute (GTRI), and the Director of Technical Initiatives at the Petit Institute for Bioengineering and Bioscience (IBB) at Georgia Tech.

Balakirsky’s research interests include robotic architectures, planning, bio-automation, robotic standards, and autonomous systems testing. His work in knowledge driven robotics couples real-time sensors and knowledge repositories to allow for flexibility and agility in robotic systems ranging from assembly and manufacturing systems to surveillance and logistics systems. The framework promotes software reuse and the ability to detect and correct for execution errors.

Previously, Balakirsky worked as a project manager at the National Institute of Standards and Technology (NIST) and was a senior research engineer at the Army Research Laboratory (ARL). At ARL, Balakirsky performed mobile robotics research in several areas, including command and control, mapping, human-computer interfaces, target tracking, vision processing and tele-operated control.

Ronald C. Arkin received the B.S. Degree from the University of Michigan, the M.S. Degree from Stevens Institute of Technology, and a Ph.D. in Computer Science from the University of Massachusetts, Amherst in 1987. He then assumed the position of Assistant Professor in the College of Computing at the Georgia Institute of Technology where he now holds the rank of Regents' Professor and is the Director of the Mobile Robot Laboratory. He also serves as the Associate Dean for Research in the College of Computing at Georgia Tech since October 2008. During 1997-98, Professor Arkin served as STINT visiting Professor at the Centre for Autonomous Systems at the Royal Institute of Technology (KTH) in Stockholm, Sweden. From June-September 2005, Prof. Arkin held a Sabbatical Chair at the Sony Intelligence Dynamics Laboratory in Tokyo, Japan and then served as a member of the Robotics and Artificial Intelligence Group at LAAS/CNRS in Toulouse, France from October 2005-August 2006.

Azadeh Ansari received the B.S. degree in Electrical Engineering from Sharif University of Technology, Iran in 2010. She earned the M.S and Ph.D. degrees in Electrical Engineering from University of Michigan, Ann Arbor in 2013 and 2016 respectively, focusing upon III-V piezoelectric semiconductor materials and MEMS devices and microsystems for RF applications. Prior to joining the ECE faculty at Georgia Tech, she was a postdoctoral scholar in the Physics Department at Caltech from 2016 to 2017. Ansari is the recipient of a 2017 ProQuest Distinguished Dissertation Award from the University of Michigan for her research on "Gallium Nitride integrated microsystems for RF applications." She received the University of Michigan Richard and Eleanor Towner Prize for outstanding Ph.D. research in 2016. She is a member of IEEE, IEEE Sensor's young professional committee and serves as a technical program committee member of IEEE IFCS 2018.

I am an Associate Professor in the School of Interactive Computing at Georgia Tech. I received my Ph.D. and B.S. degrees in Computer Science from Carnegie Mellon University, and held positions as a Postdoctoral Associate at the MIT Media Lab and as Assistant Professor at Worcester Polytechnic Institute prior to joining Georgia Tech. I direct the Robot Autonomy and Interactive Learning (RAIL) lab, where we work on developing robots that are able to effectively operate in human environments. My research interests span robotics and artificial intelligence, including semantic reasoning, adjustable autonomy, human computation and cloud robotics. Please visit the RAIL lab website for a description of our latest projects.

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

Ratan is an Assistant Professor of Cognition and Brain Science in the School of Psychology at Georgia Tech, and the Director of the Murty Lab (murtylab.com). He obtained his PhD from Indian Institute of Science (IISc) Bangalore and was a postdoctoral researcher in the Kanwisher and DiCarlo labs at MIT before moving to Georgia Tech. Research in the Murty Lab aims to uncover the neural codes and algorithms that enable us to see. The central theme of the lab's work is to integrate biological vision with artificial models of vision. The lab combines the benefits of closed-loop experimental testing (using 3T/7T human functional-MRI) with cutting-edge computational methods (like deep neural networks, generative algorithms, and AI interpretability) toward a new computationally precise understanding of human vision. This research also guides the development of neurally mechanistic biologically constrained models aimed to uncover a better understanding of the neurobiological changes that underlie perceptual abnormalities such as agnosias.

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.

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. 

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.