My name is Yu-Chia Chen, and I am a Research Scientist at Facebook. My research interests are in unsupervised learning, geometric data analysis, and vector field learning. Please check out my CV here.


I graduated with my Ph.D. in Electrical Engineering at the University of Washington (UW) in August 2021. I was honored to complete my thesis, Learning Topological Structures and Vector Fields on Manifolds with (Higher-order) Discrete Laplacians, under the supervision of professor Marina Meilă.

I obtained my B.S. in Physics at National Taiwan University (NTU) in June 2015. I was pleased to work with professor Yang-Fang Chen on the bio-inspired random laser.


I was at Facebook as a Machine Learning Intern in 2020. We built transfer learning and multi-task learning deep learning models to optimize the click-through rate (CTR) based recommendation system for search ads placement.

I interned at Microsoft Research during the summer of 2018. We developed modeling large-scale temporal networks by dynamic stochastic block model and its extension to causal impact on dynamic social networks. Our work has been published in KDD’19 and Animal Behaviour.


  • Jun 2020 Machine learning internship at Facebook, Seattle, WA
  • Dec 2019 Presenting at NeurIPS’19, Vancouver, Canada (12/08/19 – 12/14/19)
  • Aug 2019 Presenting at KDD’19, Anchorage, AK (08/04/19 – 08/08/19)