Kilian Weinberger is a professor in the Department of Computer Science at Cornell University. He received his Ph.D. from the University of Pennsylvania in machine learning under the supervision of Lawrence Saul, and his undergraduate degree in mathematics and computing from the University of Oxford. In 2011 he was awarded the Outstanding AAAI Senior Program Chair Award and in 2012 he received an NSF CAREER award. He is the recipient of the Daniel M. Lazar ’29 Excellence in Teaching Award (2016) and the Ann S. Bowers Teaching and Advising Excellence Award (2024). As of 2024, he is an ACM and AAAI fellow and in 2021 became a Blavatnik National Awards Finalist. Since 2024 he has been a member of the Sloan Research Fellowships Selection Committee. Weinberger’s research focuses on machine learning and its applications. In particular, he has worked on learning under resource constraints, metric learning, AI in science, computer vision, autonomous vehicles, Gaussian processes, and deep learning. Before joining Cornell University, he was an associate professor at Washington University in St. Louis, and before that, he worked as a research scientist at Yahoo! Research in Santa Clara.
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Machine Learning
Advancements, Opportunities, and Dangers
Thursday, January 09, 2020, 1pm
EST
Event Overview
Machine learning is emerging as one of today’s fastest-growing fields. As automation and artificial learning expand into nearly every industry, those who understand machine learning are sure to be in ever higher demand on the job market. And as machine learning opens up new opportunities across a number of diverse sectors, possibilities within the field seem nearly endless. But as with all new innovations, there is also the danger that its potential will be overhyped and create unrealistic expectations.
What You'll Learn
- Learn about the newest advances in machine learning and AI.
- Understand how this rapidly advancing field is creating new job opportunities.
- Explore how machine learning and AI are improving sectors like medical care, transportation, and communications.
- Discuss how machine learning may lead to false expectations, unrealistic hype, and even abuse.
Speaker
Kilian Weinberger
Professor of Computer Science
Cornell Bowers Computing and Information Science
Professor of Computer Science, Cornell Computing and Information Science
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