310K Olin Hall of Engineering
University of Southern California
Los Angeles, CA, 90089
renyuanx@usc.edu

I am currently a WiSE Gabilan Assistant Professor in the Epstein Department of Industrial and Systems Engineering at the University of Southern California. Before joining USC, I spent two years as a Hooke Research Fellow in the Mathematical Institute at the University of Oxford mentored by Professor Rama Cont. I completed my Ph.D. in IEOR Department at UC Berkeley under the supervision of Professor Xin Guo in 2019. I received my Bachelor’s degree in Mathematics from the University of Science and Technology of China in 2014. Please find my CV here.

We are organizing a World Online Seminar on Machine Learning in Finance. Please find out more here!

We are organizing the 2nd Workshop on Women in AI and Finance. Please submit a long abstract here if you are interested in presenting at this workshop and joining the network!

  • 13th September 2021: I will give a talk at the Probability/Math Finance Seminars at CMU on the Scaling Property Of Deep Residual Networks.
  • 13-17th September 2021: I will give a talk at the Workshop on Advances in Stochastic Analysis for Handling Risks in Finance and Insurance at CIRM on Multi-agent Reinforcement Learning: From A Mean-Field Perspective.
  • 21-23th September 2021: I will give a short course at the Summer School of the Bachelier Finance Society on the Connections Between Mean-field Theory And Machine Learning.
  • 4th October 2021: I will give talk at UCLA on Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approach.
  • 12th October 2021: I will give talk in the IEMS Department at Northwestern University.
  • 13th October 2021: I will give talk at BNY Mellon on Machine Learning for Market Simulators.
  • 2nd December 2021: I will give talk at the FME Early Career Seminar.
  • 18-20 December 2021: I am organizing a session at the The 15th International Conference on Computational and Financial Econometrics (CFE 2021) on Machine Learning for Finance: Theory and Application.