Welcome to THU-ATOM Lab
AI-driven TransfOrmative Medicine

Welcome to THU-ATOM Lab at the Institute for AI Industry Research (AIR), Tsinghua University.

Led by Professor Yanyan Lan, our lab is at the forefront of AI for science, focusing on pioneering research in biopharmaceuticals and healthcare. We tackle critical challenges in these fields by leveraging advanced data-driven and deep learning methods, offering solutions that surpass traditional approaches in speed, accuracy, and high-throughput capabilities.

Our research spans a broad spectrum of cutting-edge technologies, including representation learning, generative models, deep graph neural networks, and information retrieval applied to molecules and proteins.

Our grand vision is to accelerate drug design, reduce development costs, expand the boundaries of AI-enabled drug research and development, and make significant contributions to human health.

Join us and be part of this revolutionary journey!

News
Sep, 2025
Our 6 recent papers have been accepted by NeurIPS 2025, and 1 recent paper has been accepted by NeurIPS AI for Science workshop 2025.
Jul, 2025
Our 3 recent papers have been accepted by ICML GenBio workshop 2025 workshop.
Jan, 2025
Our paper "A foundation model of transcription across human cell types" has been accepted for publication in Nature.
Sep, 2024
We release the project "Drug The Whole Genome" and introduce our work in paper "Deep contrastive learning enables genome-wide virtual screening".
Aug, 2024
Our article titled "Pre-training with Fractional Denoising to Enhance Molecular Property Prediction" has been accepted for publication in Nature Machine Intelligence.
Research
Protein Structure Prediction
Design advanced protein structure prediction pipelines that have better performance than the AlphaFold.
Molecular pretraining
Develop cutting-edge self-supervised learning models for performance boost of molecular property predictions, protein structure predictions and so on.
Ultra-fast virtual screening
Seek extreme speed and accuracy of virtual screening methods to achieve genome-wide drug discovery.
Generative AI drug discovery
Leverage powers of generative models like diffusion-based generative models or autoregressive language models for molecule modification, design and evaluation.
Group
Professor
Postdoc
Postdoc
Yuying Zhang
Postdoc
Yunfan Jin
Postdoc
Wenyu Zhu
Research Assistant
Yida Cai
Research Assistant
Phd Student
Phd Student
Phd Student
Bicheng Lin
Phd Student
Quan Li
Phd Student
Kelin Wu
Phd Student
Dapeng Jiang
Phd Student
Yuanhuan Mo
Intern
Zitao Chen
Intern
Haoming Kong
Intern
Alumni
Xingsi Xie
Jianhui Wang
Yanwen Huang
Hongliang Li
Jiaxin Zheng
Yuanle Mo
Gaochao Liu
Minghao Li
Minsi Ren
Jianing Li
Recent Publications
Learning Protein-Ligand Binding in Hyperbolic Space
AANet: Virtual Screening under Structural Uncertainty via Alignment and Aggregation
Manipulating 3D Molecules in a Fixed-Dimensional SE(3)-Equivariant Latent Space
Zitao Chen*,
Zitong Tian*,
CIDD: Collaborative Intelligence for Structure-Based Drug Design Empowered by LLMs
Straight-Line Diffusion Model for Efficient 3D Molecular Generation
Haohan Chi,
Bowen Zheng,
Huan-ang Gao,
FIGRDock: Fast Interaction-Guided Regression for Flexible Docking
Bicheng Lin*,
Yuanhuan Mo*,
Wenyu Zhu,
Haitao Li,
CPSea: Large-scale cyclic peptide-protein complex dataset for machine learning in cyclic peptide design
Ziyi Yang,
Hanyuan Xie,
Yinjun Jia,
Xiangzhe Kong,
Jiqing Zheng,
Ziting Zhang,
Yang Liu,
Lei Liu,
Revisiting Sampling Strategies for Molecular Generation
Multi-Granular Contrastive Alignment and Fusion for Fragment-Enhanced Virtual Screening
How Good is AlphaFold3 at Ranking Drug Binding Affinities?
Wenyu Zhu,
Qixuan Chen,
Xiaohe Tian,
Zhengyi Zhong,
Jianhui Wang,
UniGEM: A Unified Approach to Generation and Property Prediction for Molecules
Reframing Structure-Based Drug Design Model Evaluation via Metrics Correlated to Practical Needs
Redefining the task of Bioactivity Prediction
A foundation model of transcription across human cell types
Xi Fu,
Shentong Mo,
Alejandro Buendia,
Anouchka P. Laurent,
Anqi Shao,
Maria del Mar Alvarez-Torres,
Tianji Yu,
Jimin Tan,
Jiayu Su,
Romella Sagatelian,
Adolfo A. Ferrando,
Alberto Ciccia,
David M. Owens,
Teresa Palomero,
Eric P. Xing,
Raul Rabadan
Pre-training with Fractional Denoising to Enhance Molecular Property Prediction
Yuancheng Sun,
Zhi-Ming Ma,
Qiwei Ye,
Full Publication List
Projects
Drug The Whole Genome
Jiaxin Tan,
Wenyu Zhu,
Yuan Xiao,
Yanwen Huang,
Yue Jin,
Yafei Yuan,
Jiekang Tian,
Weiying Ma,
Yaqin Zhang,
Chuangye Ye,
Wei Zhang,
Photos
Group photo of the team on Teachers' Day 2025
Team building at Baiwangshan in 2024
Group photo of the team on Teachers' Day 2024
ICLR 2024
ICLR 2024
ICLR 2024
Team building with AIR+ in Wuxi 2024
Xin Hong won the team championship in the university's faculty badminton competition
Team badminton activity
Professor Lan's birthday party in 2023
Group photo of the team on Teachers' Day 2023
Group photo of the team on Teachers' Day 2022
Contact Us
Prof. Yanyan Lan
Email: lanyanyan@tsinghua.edu.cn
Address: 12 / F, block C, Qidi science and technology building, Tsinghua Science and Technology Park, Haidian District, Beijing, 100000