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Copy file name to clipboardExpand all lines: _config.yml
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website: https://www.shirleyho.me/
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bio: Shirley Ho is a Group Leader of Cosmology & Machine Learning at Flatiron Institute, Research Professor of Physics and Affiliated Faculty of Center for Data Science at New York University. She also holds other appointments at Carnegie Mellon University and Princeton University. She is also a Fellow at the International Astrostatistics Association. She was a Senior Scientist at Berkeley Lab from 2016 to 2018 and a Cooper Siegel Chair Professor at Carnegie Mellon University from 2011 to 2016. She was a Seaborg and Chamberlain fellow at Berkeley Lab and UC Berkeley from 2009-2011 under the supervision of Prof. Martin White, Prof. David Schlegel and Prof. Uros Seljak, after receiving a PhD degree from Princeton University 2008, under the supervision of Prof. David Spergel and graduated summa cum laude with a B.A. in Physics and Computer Science from UC Berkeley. She was a National Blavatnik finalist in 2023, and was awarded the Macronix Prize (2014) and Carnegie Science Award (2015). She was also recognized by the European Physical Society Giuseppe and Vanna Cocconi Prize in cosmology 2023 for work in Sloan Digital Sky Survey BOSS survey, NASA Group Achievement Prize in 2020 and 2022 for her work in Planck and Roman Space Telescope.
bio: Jake is a PhD student in Applied Physics at Yale, supervised by Smita Krishnaswamy. His research interests include multimodal foundation models and representation learning with applications to biological datasets. Previously, Jake worked at Johns Hopkins Applied Physics Lab, and completed his undergraduate studies in Computer Science and Physics and the University of Michigan.
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- full_name: Geraud Krawezik
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tagline:
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avatar: geraud_krawezik.jpg
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website: https://marielpettee.com/
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bio: Dr. Mariel Pettee (Physics PhD, Yale University) is an interdisciplinary scientist and performing artist based in Brooklyn. She is a Chamberlain Postdoctoral Research Fellow at Lawrence Berkeley National Laboratory and a visiting researcher at the Flatiron Institute Center for Computational Astrophysics. Her scientific research encompasses the development of Machine Learning (ML) models for high-energy particle physics and cosmology that have broad applicability across other areas of science and art. Since 2017, she has been one of the pioneers of AI-generated dance, leading multiple independent teams of researchers to develop custom ML models to generate choreography based on 3D motion capture data of her own movements. Prior to her PhD, she earned her Bachelors in Physics & Mathematics from Harvard University and her Masters in Physics at the University of Cambridge as a Harvard-Cambridge Scholar.
bio: Helen Qu is a research fellow at the Center for Computational Astrophysics (CCA) at the Flatiron Institute. She is broadly interested in reinforcement learning, collective intelligence, multimodal models, and AI for science. She holds a PhD in Physics and a BSE in Computer Science from the University of Pennsylvania, specializing in machine learning methods for type Ia supernova cosmology.
bio: Liam is a Ph.D. student in physics at U.C. Berkeley, supported by the NSF Graduate Research Fellowship, and a visiting researcher at the Flatiron Institute. He has been a member of the Polymathic team since 2023. Presently, his research focuses primarily on developing large, multimodal foundation model for the physical sciences. Prior to Berkeley, he received his B.S. in physics from Princeton University and completed a predoctoral fellowship in the Center for Computational Astrophysics at Flatiron. Outside of work, Liam enjoys mountaineering, olympic-style weightlifting, and guitar.
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