I’m a computer science Ph.D. student at the University of Pennsylvania advised by Brielin C. Brown working on a scalable Bayesian causal discovery model to predict intervention effects and advance precision medicine. I also earned Statistics AM from Wharton, where I was advised by Nandita Mitra and worked on Bayesian difference in difference estimation.

Previously, I was a computational biologist at Memorial Sloan Kettering Institute, working with Quaid Morris. 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 in summer 2023, working with Bob Carpenter.

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

Papers : Google Scholar

Research

Publications

A Sensitivity Analysis in Bayesian Difference-in-Difference under parallel trend violations
Seong Woo Han, Gary Hettinger, Nandita Mitra, Arman Oganisian
In progress, 2024

Crowdsourcing with Difficulty: A Bayesian Rating Model for Heterogeneous Items
Seong Woo Han, Ozan Adiguzel, Bob Carpenter
Submitted, 2024

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

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, with Pratik Chaudhari