I’m a student researcher at Google DeepMind, working on AI co-scientist. I am also a computer science Ph.D. student at the University of Pennsylvania advised by Brielin C. Brown. I work on Bayesian causal discovery, causal representation learning, and multi-agent AI systems.

I earned Statistics AM from Wharton, where I was advised by Nandita Mitra, working on Bayesian causal inference. Previously, I completed my undergraduate studies in Mathematics at NYU, where I worked with Charlie Peskin at the Courant Institute of Mathematical Sciences.

I interned at Flatiron Institute, Center for Computational Mathematics, working on hierarchical Bayesian modeling with Bob Carpenter.

Email : seonghan [at] seas [dot] upenn [dot] edu

Papers : Google Scholar

Research

Publications

Large Scale Bayesian Causal Discovery Using Total Effect Estimates From Intervention Data
Seong Woo Han, Daniel Duy Vo, Brielin C. Brown
Submitted, 2026
[paper]

Sensitivity of the Philadelphia's beverage tax effect to violations of parallel trends: A Bayesian sensitivity analysis
Seong Woo Han, Nandita Mitra, Gary Hettinger, Arman Oganisian
Submitted, 2026
[paper]

Hierarchical Bayesian Crowdsourcing with Item Difficulty
Seong Woo Han, Ozan Adiguzel, Bob Carpenter
Symposium on Probabilistic Machine Learning, 2026
[paper]

PolyA_DB v4: systematic polyA site identification and isoform annotation in human mouse genomes using 3’ end and long-read sequencing data
Shan Yu, Wei Chun Chen, Luyang Wang, San Jewell, Ayna Mammedova, Seong Woo Han, Priyankara Wickramasinghe, Yoseph Barash, Bin Tian
Nucleic Acids Research, 2026
[paper]

Contrasting and Combining Transcriptome Complexity Captured by Short and Long RNA Sequencing Reads
Seong Woo Han, San Jewell, Andrei Thomas-Tikhonenko, Yoseph Barash
Genome Research, 2024
[paper]

Computer simulation of surgical interventions for the treatment of refractory pulmonary hypertension
Seong Woo Han, Charles Puelz, Craig Rusin, Dan Penny, Ryan Coleman, Charles S. Peskin
Mathematical Medicine and Biology, 2022
[paper]

Teaching Experience

ESE 546: Principles of Deep Learning, Fall 2022, Fall 2025 with Pratik Chaudhari