Yuan-Sen Ting

Yuan-Sen TIng

Yuan-Sen Ting

Associate Professor

ting.74@osu.edu

4015 McPherson Laboratory

Areas of Expertise

  • Machine Learning and Artificial Intelligence
  • Astrostatistics and Agentic AI Systems
  • Galactic Evolution and Galactic Archaeology
  • Large Language Models and Foundation Models
  • Stellar Spectroscopy and Stellar Evolution
  • Survey Science and Data-Driven Methods

Education

  • Ph.D. 2017, Astrophysics and Astronomy, Harvard University
  • M.A. 2014, Astrophysics and Astronomy, Harvard University
  • M.S.E. 2012, Engineer's Degree, École Polytechnique
  • M.Sc 2012, Physics, National University of Singapore
  • B.Sc 2011, Physics (minor in Mathematics), National University of Singapore

Prof. Ting joined The Ohio State University in 2024 as an Associate Professor in Astrophysics and is a faculty member at the Center for Cosmology and Astroparticle Physics. His research is at the intersection of artificial intelligence and astronomical research, combining computational methods with astronomical data to study galactic archaeology and stellar evolution. He develops machine learning techniques for analyzing large astronomical surveys, working with data from projects like SDSS, DESI, and Gaia. His work spans multiple areas including stellar spectroscopy, chemical abundance analysis, and galactic dynamics. His research includes developing foundation models and exploring agentic AI systems for astronomy, investigating how large language models can assist in astronomical research and discovery. He is also interested in cosmological parameter inference using simulation-based approaches and state-of-the-art generative models. Prof. Ting also holds an appointment as an Adjunct Scientist at the Max Planck Institute for Astronomy. He previously held positions at the Australian National University, Institute for Advanced Study, Princeton University and Carnegie Institution for Science. He is a recipient of the Alexander von Humboldt Fellowship, the NASA Hubble Fellowship, and the Australian Research Council Discovery Early Career Researcher Award (DECRA).

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