I am a Postdoc Researcher at the Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, working with Prof. Caroline Uhler and Prof. Ramnik Xavier. My research aims to bridge machine learning and biology, focusing on developing computational methods to tackle unresolved biological problems.

Publications

pdf	A structure-informed deep learning framework for modeling TCR-peptide-HLA interactions Kai Cao, Rui Li, Martin Strazar, Eric M. Brown, Phuong N.U. Nguyen, Marie-Madlen Pust, Jihye Park, Daniel B. Graham, Orr Ashenberg, Caroline Uhler, Ramnik Xavier bioRxiv, 2026    Code

pdf	CPS: Mapping Physical Coordinates to High-Fidelity Spatial Transcriptomics via Privileged Multi-Scale Context Distillation Lei Zhang, Kai Cao, Shuqiao Zheng, Shu Liang, and Lin Wan Bioinformatics, 2026 (ISMB 2026, acceptance rate: 16%), accepted, in press    Code

pdf

Generative Design of Cell Type-Specific RNA Splicing Elements for Programmable Gene Regulation Xi Dawn Chen*, Maile Jim*, Mounica Vallurupalli*, Kai Cao*, Andrea Navarro Torres, Jing Wesley Leong, Yifan Zhang, David Wollensak, Qiyu Gong, Jing Sun, Mehdi Borji, Gail Schor, Sofia Mrowka, Margaret Hu, Anisha Laumas, Jennifer A. Roth, Todd Golub, Fei Chen (*co-first authors) bioRxiv, 2025    Code

pdf	Energy-Regularized Graph Learning for Multiscale Spatial Representation Qiyu Gong, Kai Cao, Jackson A. Weir, Qitian Wu, Dongshunyi Li, Fei Chen bioRxiv, 2025    Code

pdf	scCausalVI disentangles single-cell perturbation responses with causality-aware generative model Shaokun An, Jae-Won Cho, Kai Cao, Jiankang Xiong, Martin Hemberg, Lin Wan Cell Systems, 2025    Code

pdf	Securing diagonal integration of multimodal single-cell data against ambiguous mapping Han Zhou, Kai Cao, Yang Lu Bioinformatics, 2025    Code

pdf	Graspot: A graph attention network for spatial transcriptomics data integration with optimal transport Zizhan Gao, Kai Cao#, Lin Wan# (#co-corresponding) Bioinformatics, 2024 (ECCB 2024, acceptance rate: 12%)    Code

pdf	A unified framework for single-cell data integration with optimal transport Kai Cao*, Qiyu Gong*, Yiguang Hong, and Lin Wan (*co-first authors) Nature Communications, 2022 (Editors’ Highlights)    Code

pdf	Manifold alignment for heterogeneous single-cell multi-omics data integration using Pamona Kai Cao, Yiguang Hong, and Lin Wan Bioinformatics, 2021    Code

pdf	Unsupervised Topological Alignment for Single-Cell Multi-Omics Integration Kai Cao, Xiangqi Bai, Yiguang Hong, and Lin Wan Bioinformatics, 2020 (ISMB 2020, acceptance rate: 19%)    Code

pdf	Class conditional distribution alignment for domain adaptation Kai Cao, Zhipeng Tu, and Yang Ming Control Theory and Technology, 2020

pdf	Learning implicit information in Bayesian games with knowledge transfer Guangpu Chen, Kai Cao, and Yiguang Hong Control Theory and Technology, 2020

pdf	Continuous-time distributed algorithms for solving linear algebraic equation Kai Cao, Xianlin Zeng, and Yiguang Hong Chinese Control Conference, 2017

pdf	Computation of linear algebraic equations with solvability verification over multi-agent networks X. Zeng and K. Cao Kybernetika, 2017