Andy Shen

Statistics PhD Student at UC Berkeley

I am a fourth-year PhD Candidate in Statistics at UC Berkeley. I am advised by Haiyan Huang and Sam Pimentel, and I also work with Avi Feller. I graduated from UCLA in June 2021 with my B.S. in Statistics.

My research is motivated by causal inference problems in health policy and medicine. I am interested in developing methods to help scientists make robust and transparent causal claims. I am also interested in solving data-driven problems using causal inference, machine learning, and survival analysis.

Most of my work is collaborative. I am grateful to be working alongside scientists and clinicians from Genentech, Kaiser Permanente, and the University of Pennsylvania School of Medicine. My research is supported by the NSF Graduate Research Fellowship.

I have spent many summers as a statistics intern at Los Alamos National Laboratory and most recently completed a biostatistics internship at Denali Therapeutics in summer 2023. I will join Genentech as a data science intern in summer 2025.

Feel free to connect with me via email or LinkedIn.

Recent News

  • February 2025: Our paper on sensitivity analysis for causal decompositions is published in Statistics in Medicine!

  • January 2025: Our paper on sensitivity analysis for causal decompositions received student paper awards for the 2025 International Conference on Health Policy Statistics and the 2025 Joint Statistical Meetings.

  • December 2024: Our paper on analyzing multiple sclerosis progression with volumetric MRI is now available on arXiv.