Neural Operators: A new era of scientific computing


The fabric of our daily lives, from weather forecasts to stock market predictions, from the aerodynamics of vehicles to the development of innovative materials, and even in the realms of medicine and space exploration, relies heavily on scientific and engineering computing. While superintelligence in AI has made significant strides in language processing, visual recognition, and audio analysis, its potential in the vast domain of natural sciences and engineering remains largely untapped. In this talk, we delve into the evolution of AI from neural networks to neural operators, unlocking new frontiers in advanced scientific computing. Join this talk as we explore how these cutting-edge technologies are revolutionizing our approach to understanding and modeling the complexities of the natural world, paving the way for groundbreaking discoveries and innovations.

Session Outline:

The big portion of daily industry is on scientific computing, the audience will see and perceive the potentials of AI in many sectors of industry.

Background Knowledge:

machine learning and deep learning understanding


Kamyar Azizzadenesheli has been a Research Staff at Nvidia since the Summer of 2022. Prior to his role at Nvidia, he was an assistant professor at Purdue University, department of computer science, from Fall 2020 to Fall 2022. Prior to his faculty position, he was at the California Institute of Technology (Caltech) as a Postdoctoral Scholar in the Department of Computing + Mathematical Sciences. Before his postdoctoral position, he was appointed as a special student researcher at Caltech, working with ML and Control researchers at the CMS department and the Center for Autonomous Systems and Technologies. He is also a former visiting student researcher at Caltech. Kamyar Azizzadenesheli is a former visiting student researcher at Stanford University and a researcher at Simons Institute, UC. Berkeley. In addition, he is a former guest researcher at INRIA France (SequeL team), as well as a visitor at Microsoft Research Lab, New England, and New York. He received his Ph.D. at the University of California, Irvine.

Open Data Science




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