CV - Yu Xie 谢玙

Email: [email protected]

Address: Karl-Liebknecht-Str. 32, Microsoft, 10178 Berlin, Germany

Education

2018.8 – 2023.9 Ph.D. in Applied Physics, Harvard University. Advisor: Boris Kozinsky

Thesis: Machine Learning Bayesian Force Fields and Applications to Phase Transformations.
2018.8 – 2021.11 M.S. in Applied Physics, Harvard University. Advisor: Boris Kozinsky
2014.9 – 2018.7 B.S. in Applied Mathematics, Peking University. Advisor: Zaiwen Wen

Thesis: Stomatology Big Data Structuring and a Simple Machine-Learning-based Design of Clinical Decision Support System.

2023.9 – Present Microsoft Research AI for Science Berlin. Senior researcher working on generative models of proteins.
2019.6 – 2019.8 Lawrence Livermore National Laboratory. Student intern in the Computational Chemistry and Materials Science program, advised by Dr. Rebecca K. Lindsey. Worked on active learning machine learning potential of carbon monoxide system with carbon condensation phenomenon.
2018.3 – 2018.7 Microsoft Research Asia. Student intern in the machine learning group, advised by Dr. Li Zhao and Dr. Tao Qin. Worked on reinforcement learning algorithms.
2017.7 – 2017.9 Harvard University. Research assistant in the Signal and Information Processing group, advised by Prof. Yue Lu. Worked on local minima of integer least square problem in MIMO system.

2025.2 Invited talks at VantAI seminar and Genmab seminar on BioEmu.
2024.10 Invited talk at Colloquium@T2P seminar series at Humboldt University Theoretical Transport Physics group on "Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport."
2023.1 Invited talk at Young Scientists Biweekly Seminar of Computational Simulation: "Machine learning Bayesian force field and uncertainty-aware molecular dynamics from Bayesian active learning."
2022.12 Invited talk at SciML webinar: "FLARE: Many-body Bayesian force field and uncertainty-aware molecular dynamics from Bayesian active learning."