Thursday, February 17, 2022, 4:00 pm — Videoconference / Virtual Event (see link below)
Machine Learning
Tools for scientific discovery
Carlos Xavier Soto is a machine learning researcher in the Computational Science Initiative (CSI) at Brookhaven National Laboratory (BNL). He was born in San Luis de La Paz, a small town in central Mexico, and grew up the second of six siblings in San Antonio, TX. As a first- generation student (college or otherwise), he attended Texas A&M University where he received his Bachelor of Science and Ph.D. degrees, both in Computer Engineering. His graduate research focused on perception algorithms, collaborative interfaces, and human-robot interaction for search and rescue robotics. In 2018 he joined the Machine Learning group in CSI, where he is now an associate computational scientist working on problems in machine learning and natural language processing. This has included applied research in functional genomics, nuclear physics, novel drug discovery, and nuclear nonproliferation. Much of his work currently focuses on investigating tools and techniques for better exploiting published research to inform and guide new scientific discoveries.
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