About

I am currently a Research Scientist at Meta, where I work with TBD Labs, AI & Systems Co-Design, and Applied AI Engineering to improve optimization and training stability for frontier AI model pre-training. Previously, in Central Applied Science at Meta, I invented a fast probabilistic model, contributed to neural network training efficiency, lead weekly reading groups and ambitious research projects on scaling laws, and mentored a Research Scientist Intern.

Before working in industry, I completed my PhD in the Computational and Biological Learning Lab at the University of Cambridge, where I worked on probabilistic machine learning under the supervision of José Miguel Hernández-Lobato. During my PhD, I was funded by the Harding Distinguished Postgraduate Scholars Programme and affiliated with the Empirical Inference department at the Max Planck Institute for Intelligent Systems. Before starting my PhD, I received my B.Sc. in Computer Science and M.Sc. in Autonomous Systems from TU Darmstadt in Germany, where I worked with Stefan Roth, Jan Peters and Kristian Kersting. I also attended The University of British Columbia, Stanford University and Aalto University as a visiting student, and participated in Fulbright’s Leaders in Entrepreneurship program.