Dr. Dellaert does research in the areas of robotics and computer vision, which present some of the most exciting challenges to anyone interested in artificial intelligence. He is especially keen on Bayesian inference approaches to the difficult inverse problems that keep popping up in these areas. In many cases, exact solutions to these problems are intractable, and as such he is interested in examining whether Monte Carlo (sampling-based) approxIMaTions are applicable in those cases.

Edmond Chow is a Professor in the School of Computational Science in the College of Computing. He previously held positions at D. E. Shaw Research and Lawrence Livermore National Laboratory. His research is in developing and applying numerical methods and high-performance computing to solve large-scale scientific computing problems and seeks to enable scientists and engineers to solve larger problems more efficiently using physical simulation. Specific interests include numerical linear algebra (preconditioning, multilevel methods, sparse matrix computations) and parallel methods for quantum chemistry, molecular dynamics, and Brownian/Stokesian dynamics.  Chow earned an Honors B.A.Sc. in systems design engineering from the University of Waterloo, Canada, in 1993, and a Ph.D. in computer science with a minor in aerospace engineering from the University of Minnesota in 1997. Chow was awarded the 2009 ACM Gordon Bell prize and the 2002 Presidential Early Career Award for Scientists and Engineers (PECASE).

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.

Dr. Braunstein developed Georgia Tech’s first health informatics courses — a graduate seminar offered on campus, an OMSCS elective and an undergraduate VIP project course. In all three courses, students work under the mentorship of domain experts to develop Fast Healthcare Interoperability Resources (FHIR) based apps for providers, patients, public health and other FHIR use cases. He also developed the first two public health informatics Massive Open Online Courses (MOOCs) and a three-course health informatics professional certificate on edX. 

In 2018 and 2019, he developed a similar course at the University of Queensland (UQ) as a Visiting Scientist at the Australian E-Health Research Centre (AEHRC), the health informatics laboratory within CSIRO, the Australian national research organization. He returned to Australia as a Visiting Scientist in 2022 and has also been working with AEHRC and UQ on an innovative, informatics-based approach to Case Based Learning in medical education. 

He is a frequent speaker at academic and industry meetings. The second edition of his textbook, Health Informatics on FHIR: How HL7’s API is Transforming Healthcare, was published by Springer in 2022 and is the first book devoted to the current and future impact of FHIR on healthcare in the US and worldwide.

Michael L. Best is Executive Director of the Institute for People and Technology (IPaT) and Professor with the Sam Nunn School of International Affairs and the School of Interactive Computing at Georgia Institute of Technology where he directs the Technologies and International Development Lab. He holds a Ph.D. from MIT and has served as director of Media Lab Asia in India and head of the eDevelopment group at the MIT Media Lab.
 

Research Fields:
* Information and Communications Technologies for Development
* International Diffusion and Innovation in IT

Geographic Focuses:
* Africa (Sub-Saharan)
* Asia (East)
* Asia (South)
* Latin America and Caribbean

Issues:
* Inequality and Social Justice
* International Development
* Digital and Mixed Media
* Digital Communication
* Human/Machine Interaction
* Internet Studies

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.

Shaowen Bardzell is Chair and Professor at Georgia Institute of Technology's School of Interactive Computing.

Bardzell holds a Ph.D. in Comparative Literature from Indiana University and pursues a humanistic research agenda within the research and practice of Human Computer Interaction (HCI). A common thread throughout her work is the exploration of the contributions of feminism, design, and social science to support technology’s role in social change. Recent research topics include care ethics and feminist utopian perspectives on IT, research through design, women’s health, posthumanist approaches to sustainable design, computational agriculture and food justice, and cultural and creative industries in Asia. Her work is supported by the National Science Foundation, Intel Corporation, and the Mellon Foundation, among others.

She is the co-editor of Critical Theory and Interaction Design (MIT Press, 2018) and co-author of Humanistic HCI (Morgan & Claypool, 2015). 

Arriaga is a Human Computer Interaction (HCI) researcher in the School of Interactive Computing. She uses psychological concepts, theories and methods to address fundamental topics of HCI and Social Computing. Her current research interests are in the area of chronic care management and mental health. She designs mHealth systems that address gaps in chronic care and mental health management. The computational systems she designs: foster engagement, facilitate continuity of care, promote patient self-advocacy, and mediate communication between patient and healthcare providers.

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.