Al Bovik
Director, UT Austin-Amazon Science Hub

Professor Al Bovik is the director of the UT Austin-Amazon Science Hub and holds the Cockrell Family Endowed Regents Chair in Engineering in the Chandra Family Department of Electrical and Computer Engineering in the Cockrell School of Engineering at UT Austin. He is also director of the Laboratory for Image and Video Engineering (LIVE) and a member of the Wireless Networking and Communication Group (WNCG), as well as the Institute for Neuroscience. His work in digital mediums, such as image and video processing, photography and television, optimizes streaming video and social media for billions of users worldwide.

Son Tran
Principal Applied Scientist, Amazon Prime Video

Son Tran is a principal applied scientist for Amazon, where he leads science efforts in multimodal learning, including vision-language pre-training, video-language representation and foundation models for video understanding. Tran also builds multimodal generative capabilities such as image generation and previously launched visual search products such as scene text recognition, product matching and Shop the Look at Amazon. His previous positions include work as a senior SDE at Microsoft and chief scientist at TrustingSocial. Tran received his Ph.D. in computer vision from the University of Maryland and continues to be published regularly in conferences such as CVPR, ICCV, ECCV, NeurIPS, WACV and KDD.

Alex Mackin
Senior Applied Scientist, Amazon Prime Video

Alex Mackin is a senior applied scientist at Amazon Prime Video, where he leads the research, development and implementation of high-performing and scalable algorithms for media defect detection. Prior positions include time as the image processing sector head in AI research and computer vision at MBDA and chief technology officer of RIDLE, a startup specializing in resilient video compression. Mackin completed his Ph.D. in electrical and electronic engineering at the University of Bristol in 2017. His thesis focused on the human impact of new immersive video formats such as high frame rate (HFR) and ultra-high definition (UHD). Additionally, Mackin leads Amazon’s external collaboration with universities and is a co-chair of the BMVA Sullivan Thesis prize.

Greg Durrett
Assistant Professor, The University of Texas at Austin

Greg Durrett is an assistant professor of computer science at The University of Texas at Austin. His research focuses on techniques for text accessing and reasoning about knowledge in text. Large language models (LLMs) like ChatGPT and GPT-4 have dramatically advanced the frontiers in this area; currently, his team is looking at where these systems succeed and fail and how to enhance their capabilities, particularly via systems that use LLMs as primitives. He is a 2023 Sloan Research Fellow and a recipient of the 2022 NSF CAREER award, among other grants from agencies including the NSF, Open Philanthropy, DARPA, Salesforce and Amazon. He completed his Ph.D. at UC Berkeley, where he was advised by Dan Klein, and he was previously a research scientist at Semantic Machines.

Cheng-Hao Kuo
Senior Applied Science Manager, Amazon

Cheng-Hao Kuo is a senior manager of applied science at Amazon, where he leads a team of researchers and engineers developing computer vision and machine learning algorithms for a variety of applications, including object detection, tracking, segmentation, recognition and reconstruction. With over 15 years of extensive experience in computer vision research and development, he has co-authored numerous papers in top-tier conferences and US patents. Kuo received his B.S. from National Taiwan University, his M.S. from Carnegie Mellon University and his Ph.D. from the University of Southern California.

Todd Humphreys
Professor, The University of Texas at Austin

Todd E. Humphreys holds the Ashley H. Priddy Centennial Professorship in Engineering in the Department of Aerospace Engineering and Engineering Mechanics at the University of Texas at Austin. He is the director of the Wireless Networking and Communications Group and of the UT Radionavigation Laboratory. He specializes in the application of optimal detection and estimation techniques to problems in secure, collaborative, and high-integrity automated situational awareness. Humphreys’ awards include The University of Texas Regents' Outstanding Teaching Award, the National Science Foundation CAREER Award, the Institute of Navigation Thurlow Award, the Walter Fried Award, and the Presidential Early Career Award for Scientists and Engineers (PECASE). He is a Fellow of the Institute of Navigation and of the Royal Institute of Navigation. Humphreys earned his B.S. and M.S. in Electrical and Computer Engineering from Utah State University and his Ph.D. in Aerospace Engineering from Cornell University.

Diana Marculescu (Moderator)
Chair, Chandra Department of Electrical and Computer Engineering

Diana Marculescu is a professor and Chair of the Chandra Family Department of Electrical and Computer Engineering at the University of Texas at Austin. She is also the Founding Director of the iMAGiNE Consortium on Intelligent Machine Engineering, a joint industry-university partnership focusing on engineering the machines that support intelligent applications from cloud to edge. Prior to joining UT, Marculescu was a professor, the Founding Director of the College of Engineering Center for Faculty Success, and Associate Head for academic affairs in ECE, all at Carnegie Mellon University. Her research interests include energy- and reliability-aware computing, hardware-aware machine learning, and computing for sustainability and natural science applications. Marculescu has received multiple recognitions, including best paper awards, the Carnegie Institute of Technology George Tallman Ladd Research Award, the Marie R. Pistilli Women in EDA Achievement Award and the Barbara Lazarus Award from Carnegie Mellon University. She received the Dipl.Ing. degree in computer science from the Polytechnic University of Bucharest and her Ph.D. in computer engineering from the University of Southern California. Marculescu is a Fellow of ACM, IEEE and AAAS.

James Bornholt
Assistant Professor, The University of Texas at Austin

James Bornholt is an assistant professor in the Department of Computer Science at The University of Texas at Austin and an Amazon Scholar at Amazon Web Services. His research focuses on techniques for building more reliable software using automated programming tools: verification tools that check program correctness and synthesis tools that generate correct programs from specifications. His work has received best paper awards at SOSP and OSDI and two IEEE Micro Top Picks selections. At Amazon Web Services, he works on reliability and performance for the Amazon S3 object storage service. Bornholt received a Ph.D. in computer science from the University of Washington.

Matt Lease
Professor, The University of Texas at Austin

Matt Lease is a professor in the School of Information at The University of Texas at Austin, a distinguished member of the ACM, a senior member of the AAAI and an Amazon Scholar in AWS AI. Lease is also a faculty founder and leader of UT Austin's Good Systems, an eight-year, $10 million University-wide grand challenge to develop responsible artificial intelligence technologies for important societal challenges. Lease’s research spans AI modeling and human-computer interaction design across applications in human computation, natural language processing and information retrieval. A theme of his ongoing work is content moderation: automated, human-in-the-loop, and human-safe practices to curb fake news, hate speech and societal polarization. Lease received his M.S. and Ph.D. from Brown University, both in computer science.

James Thompson
Principal Research Scientist, Amazon

James Thompson is a principal research scientist at Amazon, where he works on containers, using statistics and machine learning to design new products and improve the experience of Amazon customers. He was born in Austin, where he spent his formative years, and is a proud alumnus of the LBJ Science Academy, Kealing Middle School and Patton Elementary. Thompson has two degrees from the Rochester Institute of Technology and a Ph.D. from the University of Washington, where he used machine learning and evolutionary principles to model protein structures. His current research interests include machine learning, causal inference, and open-source software. Thompson lives in Seattle with his wonderful partner, two delightful children and an undisclosed number of mischievous cats.

Neeraja Yadwadkar
Assistant Professor, The University of Texas at Austin

Neeraja Yadwadkar is an assistant professor in the Chandra Family Department of Electrical and Computer Engineering at The University of Texas at Austin and is also an affiliated researcher with VMware Research Group. Her research straddles the boundaries of computer systems and machine learning. Previously, Yadwadkar was a post-doctoral research fellow in the Computer Science Department at Stanford University. She graduated with a Ph.D. in computer science from the RISE Lab at the University of California, Berkeley, where she wrote her dissertation on automatic resource management in the data center and the cloud. Before starting her Ph.D., Yadwadkar received her M.S. in computer science from the Indian Institute of Science, Bangalore, India, and her B.S. from the Government College of Engineering, Pune.

Maytal Saar-Tsechansky
Professor, The University of Texas at Austin

Maytal Saar-Tsechansky is the Mary John and Ralph Spencer Centennial Professor at the McCombs School of Business at The University of Texas at Austin. Her research focuses on advancing artificial intelligence methods to improve decision-making and to benefit people, organizations and society. Saar-Tsechansky's recent work focuses on human-AI collaboration and trustworthy AI with the overarching goal of bringing to bear human, organizational, and societal goals and constraints to catalyze AI systems’ positive impact in the world. This agenda includes AI systems that cost-effectively learn from imperfect and biased humans, and advancing AI towards human-AI teams tasked with low- and high-stakes decision-making, involving both predictions and course of action choices. Her work has been supported by government and industry, including the National Science Foundation and the Israeli Science Ministry. She leads the University of Texas at Austin’s Translational AI initiative and is an academic board member of the University’s Machine Learning Lab. Saar-Tsechansky received her B.S. and M.S. from Ben-Gurion University, Israel and her Ph.D. from the Leonard N. Stern School of Business at New York University.

Amit Kumar
Assistant Professor, The University of Texas at Austin

Amit Kumar is an assistant professor of marketing and psychology at The University of Texas at Austin’s McCombs School of Business. His research focuses on the scientific study of happiness and has been featured in dozens of media outlets, including The New York Times, NPR, The Wall Street Journal, National Geographic, Time magazine and The Washington Post. Kumar's scholarly work as also appeared in many peer-reviewed publications such as The Journal of Consumer Psychology, The Journal of Experimental Psychology and Psychological Science. Prior to joining Texas McCombs, Kumar completed his postdoctoral fellowship at the University of Chicago’s Booth School of Business. He received a Ph.D. in social psychology from Cornell University and his A.B. in psychology and economics from Harvard University.

Gérard Medioni
Vice President, Distinguished Scientist, Amazon

Gérard Medioni is a vice president/distinguished scientist at Amazon, where he is leading the research efforts for Amazon Just Walk Out, the Amazon One service and the recently opened Amazon Style store. Medioni is also a professor emeritus of computer science at USC, where he served as chair of the Department of Computer Science from 2001 to 2007. Medioni has made significant contributions to the field of computer vision. He has published four books, over 80 journal papers and 200 conference articles; he is also the recipient of more than 90 patents. Medioni is the editor, along with Sven Dickinson, of the book series Computer Vision for Morgan-Claypool. Medioni is on the advisory board of the IEEE Transactions on PAMI journal as well as the Image and Vision Computing journal. He received the Diplôme d’Ingenieur from ENST, Paris, in 1977, as well as his M.S. and Ph.D. from the University of Southern California in 1980 and 1983, respectively.

Al Bovik
Director, UT Austin-Amazon Science Hub

Professor Al Bovik is the director of the UT Austin-Amazon Science Hub and holds the Cockrell Family Endowed Regents Chair in Engineering in the Chandra Family Department of Electrical and Computer Engineering in the Cockrell School of Engineering at UT Austin. He is also director of the Laboratory for Image and Video Engineering (LIVE) and a member of the Wireless Networking and Communication Group (WNCG), as well as the Institute for Neuroscience. His work in digital mediums, such as image and video processing, photography and television, optimizes streaming video and social media for billions of users worldwide.