Event Description

Selected as the National AI Institute for Foundations of Machine Learning (IFML) by the National Science Foundation (NSF) in 2020, we are partnering with the Texas Advanced Computing Center (TACC) to widen the knowledge and teaching of Machine Learning and AI in High Schools. 

Presented by Joydeep Biswas.

Artificial Intelligence and Machine Learning have grown in popularity recently, fueled by recent successes in several domains, including image recognition, decision making, and robotics. But what actually constitutes "artificial intelligence"? How is "machine learning" related? What are the open challenges, limitations, and ongoing research in these areas? How did it all begin, and where are we heading? This talk will cover an introduction to AI and ML, including a historical perspective, and will offer some ways to think about these questions.

Joydeep Biswas is an assistant professor in the department of computer science at the University of Texas at Austin. He earned his B.Tech in Engineering Physics from the Indian Institute of Technology Bombay in 2008, and M.S. and PhD in Robotics from Carnegie Mellon University in 2010 and 2014 respectively. His research spans perception and planning for long-term autonomy, with the ultimate goal of having service mobile robots deployed in human environments for years at a time, without the need for expert corrections or supervision.

Logistics

A Zoom link will be sent to registrants prior to the webinar.

Schedule

Monday, June 14, 2021

10:00-11:00am Central Time

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You can view the full list of webinars and recordings on our AI / ML Webinar Series page at https://utakeit.tacc.utexas.edu/r/AI_ML_webinars_2021/ 

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About the Institute for Foundations of Machine Learning - a National AI Research Institute

Designated by the National Science Foundation (NSF) in 2020, we are the National AI Institute for Foundations of Machine Learning (IFML). We develop the key foundational tools for the next decade of AI innovation leveraging the combined forces of The University of Texas at Austin, University of Washington, Wichita State University, and Microsoft Research. Our researchers create new algorithms that can help machines learn on the fly, change their expectations as they encounter people and objects in real life, and even bounce back from deliberate attempts by adversaries to manipulate datasets.

This program is supported by the National Science Foundation Award FAIN 2019844.