My name’s Jianle Sun (孙健乐, Mandarin IPA /suən˥˥·tɕjɛn˥˩·lɤ˥˩/). I am a PhD student in Logic, Computation, and Methodology at Carnegie Mellon University. Before this, I obtained my M.S. and B.S. degree from the Department of Bioinformatics and Biostatistics, Shanghai Jiao Tong University. I am working on the intersection of statistics, machine learning, and computational biology (like genetics, genomics, and epidemiology).

Reseach interests

• Causal inference and learning. I am dedicated to developing methods for learning causal relationships from data and performing personalized counterfactual inference, which bridges many active areas in statistics and machine learning, such as semiparametric estimation, conditional copulas, disentangled representation learning, generative model and optimal transport.
• Computational biology: Statistical genetics (GWAS, eQTL, etc.) and genomics (single-cell and spatial omics, etc.).
• Foundation models in biology: Genomics language model, single-cell foundation model, etc.

You can find the list of my publications and read the papers here.

I am happy with collaboration on theory (asymptotic properties, uncertainty quantification), methodology (representation learning, effect estimation, counterfactual generation), and application (genetics, genomics, epidemiology).