Naveena Karusala is an assistant professor in the School of Interactive Computing at Georgia Tech. Her research investigates how we can center care work in the design of AI technologies to enable sustainable futures of work, with a focus on the domains of healthcare and social services. Her work has received recognition at premier venues for Human-Computer Interaction, such as ACM CHI and ACM CSCW. She holds a PhD in Computer Science from the University of Washington, and a Bachelor's in Computer Science from Georgia Tech. Naveena also serves on the ACM SIGCHI Executive Committee as Vice-President for Communications.

I am an Assistant Professor at Georgia Institute of Technology’s School of Interactive Computing. I design culturally informed STEM education technologies and increase access to computer science education in sustainable ways for low-income students and underserved communities. My work prioritizes identity development, engagement, and long-term sustainability of interventions.

Prior to Georgia Tech, I was a post-doctoral researcher at Carnegie Mellon’s Robotics Academy. I have a PhD in Human-Computer Interaction from Carnegie Mellon’s HCI Institute and was advised by Amy Ogan and Ken Koedinger.

My research has contributed to the design of a tablet-based learning system used to supplement formal education by over 500 students in rural Tanzania, programmable video games codesigned with children to increase computational thinking and coding skills among low income and marginalized youth in the United States, codesign of a state-wide Artificial Intelligence middle school curriculum, and active collaboration with several schools and organizations. As a passion project, I review children’s storybooks that celebrate African history and culture.

Kexin Rong is an assistant professor in the School of Computer Science at Georgia Tech. She is broadly interested in developing systems and tools to help simplify large-scale data analytics, i.e., making it easy for non-experts to utilize their large and complex datasets, by synthesizing techniques from data management, machine learning, and human-computer interaction. She is part of the Georgia Tech database group. She received a Ph.D. in Computer Science from Stanford University in 2021 and a B.S. in Computer Science from the California Institute of Technology in 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.

Annie Anton, Ph.D., is a professor in the School of Interactive Computing at Georgia Tech, which she chaired until 2017. Previously, she served as a professor in the Computer Science Department of the College of Engineering at North Carolina State University, where she was director of the CSC Policy and Compliance Initiative and a member of the NCSU Cyber Defense Lab. In 2010, she chaired the NC State University Reappointment, Promotion and Tenure Committee. In 2008, she chaired the NC State Public Policy Task Force. Anton's research focuses on methods and tools to support the specification of complete, correct behavior of software systems used in environments that pose risks of loss as a consequence of failures and misuse. This includes systems in which the security of personal and private information is particularly vulnerable. Current extensions to this work, include the analysis of federal security and privacy regulations, and compliance practices. Anton is the founder and director of ThePrivacyPlace.org, a research group of students and faculty at Georgia Tech, CMU, NC State and UMBC. This group is interested in technologies that assist practitioners and policy makers in meeting the challenge of eliciting and expressing policies and regulations (a form of requirements). These tools help ensure that software systems are aligned with the privacy polices and regulations that govern these systems. Her professional activities include a notable combination of multi-disciplinary research and education. She is co-founder of the annual Requirements Engineering and the Law Workshop (RELAW). She is a former associate editor for IEEE Transactions on Software Engineering, cognitive issues subject area editor for the Requirements Engineering Journal, and the International Board of Referees for Computers & Security. Antón has served on various boards, ﾠincluding: ﾠPresident Obama's Commission on Enhancing National Cybersecurity, the NIST Information Security & Privacy Advisory Board, the IEEE Computer Society Research Board, an Intel Corporation Advisory Board, the Future of Privacy Forum Advisory Board. ﾠShe is a former member of the U.S. DHS Data Privacy and Integrity Advisory Committee, the CRA Board of Directors, the NSF Computer & Information Science & Engineering Directorate Advisory Council, the Distinguished External Advisory Board for the TRUST Research Center at U.C. Berkeley, the DARPA ISAT Study Group, the USACM Public Policy Council, the Advisory Board for the Electronic Privacy Information Center in Washington, D.C., the Georgia Tech Alumni Association Board of Trustees, the Microsoft Research University Relations Faculty Advisory Board, the CRA-W, the Georgia Tech Advisory Board (GTAB), and Corporate Secretary for Trekking for Kids, Inc.

David V. Anderson received the B.S and M.S. degrees from Brigham Young University and the Ph.D. degree from Georgia Institute of Technology (Georgia Tech) in 1993, 1994, and 1999, respectively. He is currently a professor in the School of Electrical and Computer Engineering at Georgia Tech. Anderson's research interests include audio and psycho-acoustics, machine learning and signal processing in the context of human auditory characteristics, and the real-time application of such techniques. His research has included the development of a digital hearing aid algorithm that has now been made into a successful commercial product. Anderson was awarded the National Science Foundation CAREER Award for excellence as a young educator and researcher in 2004 and the Presidential Early Career Award for Scientists and Engineers in the same year. He has over 150 technical publications and 8 patents/patents pending. Anderson is a senior member of the IEEE, and a member the Acoustical Society of America, and Tau Beta Pi. He has been actively involved in the

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.

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.