I am a final-year doctoral student in computer science at Carnegie Mellon University. I am advised by Prof. Jan Hoffmann. My research focuses are programming languages, quantitative verification, and probabilistic programming; my broader interests include type theory, program synthesis, concurrency, and Bayesian inference.

I completed my undergraduate at Peking University, China where I worked with Prof. Yingfei Xiong on summarization techniques to analyze programs sharing big libraries.

Here is my Curriculum Vitae.

News

• I am on the academic job market for 2022 positions. Please reach out to me if you think I would be a good fit for your department.
• I’m excited that our papers Sound Probabilistic Inference via Guide Types and Central Moment Analysis for Cost Accumulators in Probabilistic Programs with Jan and Tom have been conditionally accepted to PLDI 2021.
• Our technical report about Probabilistic Resource-Aware Session Types is available on arXiv.
• Our articles Liquid Resource Types and Raising Expectations: Automating Expected Cost Analysis with Types have been accepted to ICFP 2020.
• Check out our recent MFPS paper on A Denotational Semantics for Low-Level Probabilistic Programs with Nondeterminism with Jan and Tom.
• Great news: Our paper on Resource-Guided Program Synthesis has been conditionally accepted to PLDI 2019.
• I’m excited that our paper Type-Guided Worst-Case Input Generation with Jan Hoffmann has benn accepted to POPL 2019.
• Check out my talent show Chengdu on SCS Day 2018!
• I’m excited that our paper PMAF: An Algebraic Framework for Static Analysis of Probabilistic Programs (with Jan Hoffmann and Tom Reps) has been conditionally accepted to PLDI 2018.