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Thomas Hofweber at Carolina Data Science Now
May 25 @ 12:00 pm - 1:00 pm
The event will feature three lightning talks by professors and researchers in UNC-Chapel Hill’s academic community, centered around the study, use, and applications of artificial intelligence in the fields of philosophy, pathology, and physics. These talks will be followed by a guided panel, an opportunity for questions and answers with the speakers, and a discussion with the data science community at UNC-Chapel Hill.
Those interested in attending can register on the Carolina Data Science Now website.
This month’s speakers include:
- Thomas Hofweber, Philosophy: Dr. Thomas Hofweber a professor of philosophy at UNC and the director of the AI Project. He works in metaphysics, the philosophy of language, and the philosophy of mathematics, with a particular emphasis on ontology and on the role of conceptual and linguistic representation in metaphysics. He regularly teaches a class entitled “AI and the future of humanity.”
- Aobo Li, Physics and Astronomy: Dr. Aobo Li received his B.S. in physics at the University of Washington in 2015, then did his graduate work at Boston University as part of the KamLAND-Zen collaboration. After getting his Ph.D. in 2020, Aobo joined UNC Chapel Hill as a Postdoctoral Research Associate and COSMS Fellow. Aobo has received many awards, including the American Physical Society 2023 Dissertation Award in Nuclear Physics, the UNC Postdoctoral Award of Research Excellence, and the NeurIPS 2022 ML4PS Workshop Outstanding Paper Award.
- Katie Newhall, Mathematics: Dr. Katie Newhall is an associate professor of mathematics at the University of North Carolina at Chapel Hill working on a diverse set of interdisciplinary applied math problems ranging from magnetic systems to granular media and active matter. She is tackling difficult problems in the field of stochastic dynamics to understand the large-scale and long-time behavior of physical and biological systems described by high-dimensional equations that evolve randomly in time. The mathematical problems she works on also help to explain experimentally observable phenomena, exposing the underlying mechanisms to intuitively explain the system’s behavior.