Hanqun Cao

Hanqun Cao(Hank)

Final-year Ph.D. Candidate, Computer Science & Engineering, CUHK
Former Visiting Researcher, Perelman School of Medicine, UPenn

About

I am on the job market for faculty, postdoctoral, and industry research positions. Get in touch →I am a final-year Ph.D. candidate in the Department of Computer Science and Engineering at The Chinese University of Hong Kong, advised by Prof. Pheng-Ann Heng. From June 2025 to August 2026, I was a visiting researcher at the University of Pennsylvania Perelman School of Medicine, working with Prof. Cesar de la Fuente-Nunez in the Machine Biology Group. I also work closely with Prof. Pranam Chatterjee on peptide design.

My research develops deep generative models and reinforcement learning methods for biomolecular design. I build AI systems that design functional proteins, antimicrobial peptides, RNA, and small molecules — and validate them experimentally. Recently, I have focused on protein design through the lens of dynamics: shaping conformational ensembles and molecular interactions, and connecting changes at the protein level to cellular responses. I hold a B.Sc. in Mathematics from CUHK and 2 US patents. My work has appeared in or been accepted by Nature Medicine, Nature Communications, Nature Machine Intelligence, Nature Computational Science, Cell Reports Physical Science, IEEE TKDE, NeurIPS, ICLR, ICML, EMNLP, ICCV, and MICCAI.

News

2026.09Accepted3 papers accepted at NeurIPS 2026: AlloGen (first) and 2 papers on RNA inverse folding and design (one co-first). AlloGen's conformation-selective binders were experimentally validated on calmodulin.
2026.09Accepted2 papers (first) accepted by Cell Reports Physical Science.
2026.09AcceptedMAGIS accepted by Nature Medicine.
2026.09Accepted1 paper (co-first) accepted at EMNLP 2026.
2026.05Accepted1 paper (first) selected as an Oral at the ICML 2026 AI4Science Workshop.
2026.05Accepted4 papers accepted at the ICML 2026 GenBio Workshop, including 1 Oral.
2026.05Accepted2 papers accepted at KDD 2026 (one first, one co-first), including CA-DEL as an Oral in the Datasets & Benchmark Track.
2026.05Accepted3 papers (first/co-first) accepted at ICML 2026.

Selected Publications

Selected work. Full list on Google Scholar.  * equal contribution  # corresponding

Protein / peptide design
AlloGen: Conformation-Selective Binder Design with Differential State Scoring
Hanqun Cao, Aastha Pal, Sumi Kimura, Yesol Kim, Jingjie Zhang, Pheng-Ann Heng, Pranam Chatterjee
NeurIPS 2026
AgentFold: Closed-Loop Agentic Search for Protein Folding Model Design
Mingquan Liu*, Jiangyu Chen*, Hanqun Cao*, Xujun Zhang, Pengsen Ma, Xiangru Tang, Shuting Jin, Annie Zheng, Zhuo Yang, Tianfan Fu, Fang Wu, Xiangxiang Zeng
EMNLP 2026
Lightweight MSA Design Advances Protein Folding From Evolutionary Embeddings (PLaME)
Hanqun Cao, Xinyi Zhou, Zijun Gao, Chenyu Wang, Xin Gao, Zhi Zhang, Chang-yu Hsieh, Cesar de la Fuente-Nunez, Chunbin Gu, Ge Liu, Pheng-Ann Heng
Cell Reports Physical Science, 2026
TD3B: transition-directed discrete diffusion for allosteric binder generation
Hanqun Cao, Aastha Pal, Sophia Tang, Yinuo Zhang, Jingjie Zhang, Pheng-Ann Heng, Pranam Chatterjee
ICML 2026 · Spotlight
Proteo-R1: reasoning foundation models for de novo protein design
Fang Wu*, Weihao Xuan*, Heli Qi*, Hanqun Cao*, Heng-Jui Chang*, Zeqi Zhou*, ..., Pheng-Ann Heng, ..., Jure Leskovec, Yejin Choi
ICML 2026
Learning the PTM code through a coarse-to-fine, mechanism-aware framework
Jingjie Zhang*, Hanqun Cao*, Zijun Gao, ..., Chang-Yu Hsieh, Chunbin Gu
Nature Communications, 2026
The forgetting-learning trade-off: making reinforcement learning work for protein language models
Hanqun Cao, Hongrui Zhang, Junde Xu, Zhou Zhang, Lingdong Shen, Minghao Sun, Ge Liu, Jinbo Xu, Wu-Jun Li, Jinren Ni, Cesar de la Fuente-Nunez, Tianfan Fu, Shuting Jin, Pheng-Ann Heng, Fang Wu
KDD 2026 · AI4Sciences Track
SF-Cluster: frustration-aware MSA subsampling for protein conformation modeling
Hanqun Cao, Zijun Gao, Chunbin Gu, Ge Liu, Pheng-Ann Heng, Pranam Chatterjee
ICML 2026 AI4Science Workshop · Oral
Structure-guided reinforcement learning for high-affinity antibody design
Hanqun Cao, Shuaike Shen, Weihao Xuan, Jian Ma, Pheng-Ann Heng, Fang Wu
ICML 2026 GenBio Workshop
Bi-TEAM: a unified cross-scale representation learning framework for chemically modified biomolecules
Chunbin Gu*, Zijun Gao*, ..., Hanqun Cao#, Jiajun Bu#, Chang-Yu Hsieh#
arXiv, 2026 · Preprint
A deep reinforcement learning platform for antibiotic discovery
Hanqun Cao, Marcelo D.T. Torres, Jingjie Zhang, Zijun Gao, Fang Wu, Chunbin Gu, Jure Leskovec, Yejin Choi, Cesar de la Fuente-Nunez, Guangyong Chen, Pheng-Ann Heng
bioRxiv, 2025 · Preprint
ODesign: a world model for biomolecular interaction design
Odin Zhang, ..., Hanqun Cao, ..., et al.
arXiv, 2025 · Preprint
GLID²E: a gradient-free lightweight fine-tune approach for discrete biological sequence design
Hanqun Cao, Haosen Shi, Chenyu Wang, Sinno Jialin Pan, Pheng-Ann Heng
NeurIPS 2025
SAGEPhos: sage bio-coupled and augmented fusion for phosphorylation site detection
Jingjie Zhang*, Hanqun Cao*, Zijun Gao, Xiaorui Wang, Chunbin Gu
ICLR 2025
InstructPLM: aligning protein language models to follow protein structure instructions
Jiezhong Qiu*, Junde Xu*, Jie Hu*, Hanqun Cao*, et al.
bioRxiv, 2024 · Preprint
RNA design
Pareto Preference Optimization for Structure- and Stability-Aware RNA Inverse Folding
Minghao Sun*, Hanqun Cao*, Zhou Zhang*, Chen Wei, Liang Wang, Tianrui Jia, Zhiyuan Liu, Tianfan Fu, Xiangru Tang, Yejin Choi, Pheng-Ann Heng, Fang Wu, Yang Zhang
NeurIPS 2026
Multi-Oracle Agreement Reveals the Limits of Self-Consistency Evaluation in RNA Design
Minghao Sun, Hanqun Cao, Fang Wu, Zhou Zhang, Zhiyuan Liu, Tianfan Fu, Pheng-Ann Heng, Yang Zhang
NeurIPS 2026 · Evaluations & Datasets Track
RiboSphere: learning unified and efficient representations of RNA structures
Zhou Zhang*, Hanqun Cao*, Cheng Tan, Fang Wu, Pheng-Ann Heng, Tianfan Fu
ICML 2026
Base-and-sugar dual-frame flow matching for RNA co-design
Junzhe Li, Lijian Peng, Yuhao Li, Yize Zhou, Hanqun Cao, Cheng Tan, Shengchao Liu
ICML 2026 GenBio Workshop
ODesign: a world model for biomolecular interaction design
Odin Zhang, ..., Hanqun Cao, ..., et al.
arXiv, 2025 · Preprint
R3Design: deep tertiary structure-based RNA sequence design and beyond
Cheng Tan, ..., Hanqun Cao, ..., Stan Z. Li
Briefings in Bioinformatics, 2025
Deciphering RNA secondary structure prediction: a probabilistic K-rook matching perspective
Cheng Tan, Zhangyang Gao, Hanqun Cao, Xingran Chen, et al.
ICML 2024
Small molecule design
DEL-Ranking Framework for Ranking-Aware Denoising of DNA-Encoded Library Screens for Improved Affinity Prediction
Hanqun Cao, Mutian He, Ning Ma, Chang-yu Hsieh, Xiaojun Yao, Cesar de la Fuente-Nunez, Chunbin Gu, Pheng-Ann Heng
Cell Reports Physical Science, 2026
CA-DEL: an open multi-target, multi-modal benchmark for learning from DNA-encoded library screens
Mutian He*, Hanqun Cao*, Cheng Tan, Zijun Gao, Xiaojun Yao, Chunbin Gu, Pheng-Ann Heng
KDD 2026 · Datasets & Benchmark Track · Oral
ODesign: a world model for biomolecular interaction design
Odin Zhang, ..., Hanqun Cao, ..., et al.
arXiv, 2025 · Preprint
ResGen is a pocket-aware 3D molecular generation model based on parallel multiscale modelling
Odin Zhang, ..., Hanqun Cao, ..., et al.
Nature Machine Intelligence, 2023
Efficient and accurate large library ligand docking with KarmaDock
Xujun Zhang, ..., Hanqun Cao, ..., et al.
Nature Computational Science, 2023

Education & Experience

Jun 2025 –
Aug 2026
Visiting Researcher
University of Pennsylvania, Perelman School of Medicine
Machine Biology Group · Host: Prof. Cesar de la Fuente-Nunez · AI-driven antibiotic discovery
Aug 2023 –
Jul 2027
Ph.D. in Computer Science & Engineering
The Chinese University of Hong Kong
Advisor: Prof. Pheng-Ann Heng · Protein design, generative models, RL for biology
Sep 2019 –
Jul 2023
B.Sc. in Mathematics
The Chinese University of Hong Kong
SURP & UROP research scholarships · FYP with Prof. Ronald Lui
Aug 2021 –
Jun 2022
Research Assistant
CUHK CSE, Prof. Yu Li
Protein structural design with score-based diffusion models
May 2021 –
Sep 2021
Summer Research
CUHK Mathematics, Prof. Jun Zou
Inverse problems in elastic wave scattering (FEM)