Fernanda Leite

Associate Dean for Research, The University of Texas at Austin

Fernanda Leite is the associate dean for research in the Cockrell School of Engineering at The University of Texas at Austin. She is the past chair of a University-wide bridging barriers research initiative called Planet Texas 2050. Most of her research has been in building and infrastructure systems information modeling, Scan-to-BIM, visualization and collaboration technologies and circular economy in the built environment. At UT Austin, Leite has taught courses on building information modeling, project management and economics, construction safety and sustainable systems engineering.

Sujay Sanghavi

Associate Professor, The University of Texas at Austin

Sujay Sanghavi is an associate professor and holds the Fluor Centennial Teaching Fellowship in Engineering # 2 in the Department of Electrical and Computer Engineering at The University of Texas at Austin. Sanghavi joined UT Austin in July 2009. He got his Ph.D. from the University of Illinois Urbana-Champaign, and a postdoc from MIT. His research interests lie at the intersection of two central challenges in modern systems: large-scale networking and high-dimensional data analysis, with a focus on algorithm design and evaluation. Sanghavi received an NSF CAREER award in January 2010.

Kent Ken

Head of AI/ML, Amazon

Kent Ken is the head of AI/ML, Strategy and Analytics for Global Demand and Operations at Amazon Web Services (AWS). He holds a B.S. in mechanical engineering from Shanghai Jiao Tong University and an MBA from the McCombs School of Business at The University of Texas at Austin. At AWS, Ken leads a multi-discipline global team working on AI/ML application research & development, solution architecting and production deployment within B2B sales and marketing. 

Oshry Ben-Harush

Tech Lead Applied Scientist, Amazon

Oshry Ben-Harush is an AI/ML practitioner and leader with over 15 years of experience in the field. He hols a B.S. and M.S. in electrical and computer engineering from Ben-Gurion University of the Negev.

In his most recent roles at Dell, Ben-Harush served as a distinguished engineer in the corporate strategy office, where he built  a data science practice from the ground up, establishing the platform, tools, data and processes required to conduct data science at scale. He also created and developed a set of use cases to explore and optimize Dell’s operations, customer engagement, product development and market trends. Since June 2022, Ben-Harush has been working as a senior applied scientist and technical lead at Amazon Web Services (AWS), where he collaborates with cross-functional teams to develop and implement cutting-edge machine learning techniques and solutions.

Sanjay Shakkottai

Professor, The University of Texas at Austin

Sanjay Shakkottai received his Ph.D. in electrical and computer engineering from the University of Illinois at Urbana-Champaign in 2002. He received the NSF CAREER award in 2004 and was elected as an IEEE Fellow in 2014. He was a co-recipient of the IEEE Communications Society William R. Bennett Prize in 2021. He currently serves as a professor in the Chandra Family Department of Electrical and Computer Engineering at The University of Texas at Austin, and holds the Cockrell Family Chair in Engineering #15. Shakkottai is also the editor in chief of IEEE/ACM Transactions on Networking. His research interests lie at the intersection of algorithms for resource allocation, statistical learning and networks, with applications to wireless communication networks and online platforms.

Changhe Yuan

Principal Applied Scientist, Amazon Prime Video

Changhe Yuan is a principal applied scientist at Amazon Prime Video, leading research in search, recommendation, personalization and whole page optimization. Previously, he also led the development of various product relationships to help customers better navigate the enormous Amazon catalog. Prior to joining Amazon, he was a tenured associate professor at City University of New York and also at Mississippi State University. He received his Ph.D. in intelligent systems from the University of Pittsburgh and was an NSF CAREER Award winner. 

Jon Tamir

Assistant Professor, The University of Texas at Austin

Jon Tamir is an assistant professor in the Chandra Family Department of Electrical and Computer Engineering at UT Austin. He received his Ph.D. in electrical and computer engineering from UC Berkeley. His research focus spans computational medical imaging, signal processing and machine learning, with specific emphasis on magnetic resonance imaging. He is a fellow of the Jack Kilby/Texas Instruments Endowed Faculty Fellowship in Computer Engineering.

Alex Dimakis (Moderator)

Professor, Chandra Department of Electrical and Computer Engineering

Alex Dimakis is a professor and holds the Stanly P. Finch Centennial Professorship in Engineering in the Chandra Family Department of Electrical and Computer Engineering at The University of Texas at Austin. In 2009, he was a CMI postdoctoral scholar at Caltech. He received an NSF Career award in 2011, a Google faculty research award in 2012 and the Eli Jury dissertation award in 2008. He is the co-recipient of several best paper awards including the joint Information Theory and Communications Society Best Paper Award in 2012.

He is currently serving as an associate editor for IEEE Signal Processing letters. His research interests include information theory, coding theory, signal processing and networking, with a current focus on distributed storage, network coding, distributed inference and message-passing algorithms. Dimakis received his Ph.D. and M.S. in electrical engineering and computer sciences from UC Berkeley and his diploma from the National Technical University of Athens.

Ali Jalali

Principal Applied Scientist, Amazon

Jalali oversees ML/AI initiatives within Amazon’s Prime Membership division as a principal applied scientist. Prior to that, he led the Prime Video demand insights and capacity planning sciences globally. He has experience in different industries including online advertisement, high-frequency trading and clean energy and building large-scale ML/AI solutions. Jalali is passionate about privacy-preserving, unbiased and ethical artificial intelligence and real-time ML/AI applications. Jalali has a Ph.D. in computer science from The University of Texas at Austin.

Adam Klivans

Director, Machine Learning Lab at The University of Texas at Austin

Adam Klivans is the director of the Machine Learning Lab and a professor at The University of Texas at Austin. His research interests lie in machine learning and theoretical computer science, in particular, learning theory, computational complexity, pseudorandomness, limit theorems and gaussian space. Klivans also serves on the editorial board for the Theory of Computing and Machine Learning Journal. He is a recipient of the NSF Career Award.

Dan Roth

Vice President and Distinguished Scientist, Amazon

Dan Roth is a vice president and distinguished scientist at AWS AI, leading the science of generative AI. At
AWS, Roth has led the scientific effort behind the first-generation generative AI products from AWS, including CodeWhisperer, Titan Models and Bedrock.

Roth is also the Eduardo D. Glandt Distinguished Professor at the department of computer and
information science at the University of Pennsylvania and a Fellow of the AAAS, ACM, AAAI and ACL. In 2017, he was awarded the John McCarthy Award. Roth has published broadly in natural language processing, machine learning, knowledge representation and reasoning and learning theory. He was the editor-in-chief of the Journal of Artificial Intelligence Research (JAIR) and has served as a program chair and conference chair for major conferences in his research areas. While in academia, Roth has consulted on machine learning and natural language processing topics and has been involved in several startups; most recently, he was a co-founder and chief scientist of NexLP, a startup that leverages the latest advances in natural language processing, cognitive analytics and machine learning in the legal and compliance domains. Roth received his B.A. summa cum laude in mathematics from the Technion, Israel and his Ph.D. in computer science from Harvard University.

Sujay Sanghavi

Associate Professor, The University of Texas at Austin

Sujay Sanghavi is an associate professor and holds the Fluor Centennial Teaching Fellowship in Engineering # 2 in the Department of Electrical and Computer Engineering at The University of Texas at Austin. Sanghavi joined UT Austin in July 2009. He got his Ph.D. from the University of Illinois Urbana-Champaign, and a postdoc from MIT. His research interests lie at the intersection of two central challenges in modern systems: large-scale networking and high-dimensional data analysis, with a focus on algorithm design and evaluation. Sanghavi received an NSF CAREER award in January 2010.

Trishul Chilimbi

Vice President and Distinguished Scientist, Amazon

Trishul Chilimbi is a vice-president and distinguished scientist at Amazon where he leads the Stores Foundational AI organization. He has worked on LLMs for over a decade and his current focus is on building foundation AI models that are specialized for shopping and e-commerce. Prior to this, he worked on all aspects of building efficient high-performance systems, including hardware architecture design, compilers, runtime distributed systems and programming languages. Chilimbi has a B. Tech in computer science from the Indian Institute of Technology, Bombay, along with a M.S. and Ph.D. from the University of Wisconsin-Madison. 

Alan 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.

Light refreshments and networking, featuring student poster sessions.