Ma Laboratory

Jianzhu Ma 

I am an associate professor of Department of Electronic Engineering and Institute for AI Industry Research at Tsinghua University.

Before joining Tsinghua University, I was a tenure track Walther Assistant Professor of
Department of Computer Science and Department of Biochemistry
at Purdue University

Email: majianzhu <at> tsinghua <dot> edu <dot> cn

My wife's homepage.

Notice: For students in Tsinghua University, please contact me if you are interested in workinig with me.
I am looking for talanted Master students, Ph.D. students to work with in the following directions,

  • Graphical Neural Network, Deep Learning

  • Immunology, Drug Discovery

  • Bioinformatics and Computational Biology

For undergraduate and master studuents, please don't do the following: First contact me to do research and then tell me you need to focus on your homework and final.


Our main focus is to develop novel computational models for translation of patient data to precision diagnosis and treatment for complex diseases, such as cancer. We seek to advance this goal from three aspects: 1) Interpretable & Transferable Machine Learning Models 2) Systems Biology and Network Models 3) BioNLP & Text Mining 4) AI-based Drug Design.

research overview 

Selected Publications

High-resolution de novo structure prediction from primary sequence
Ruidong Wu, Fan Ding, Rui Wang, Rui Shen, Xiwen Zhang, Shitong Luo, Chenpeng Su, Zuofan Wu, Qi Xie, Bonnie Berger, Jianzhu Ma, Jian Peng
bioRxiv 2022 corresponding author

Quantifying spatial homogeneity of urban road networks via graph neural networks
Jiawei Xue, Nan Jiang, Senwei Liang, Qiyuan Pang, Takahiro Yabe, Satish Ukkusuri, Jianzhu Ma
Nature Machine Intelligence 2022 cover paper

Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients
Jianzhu Ma, Samson Fong, Yunan Luo, Christopher Bakkenist, John Paul Shen, Soufiane Mourragui, Lodewyk Wessels, Marc Hafner, Roded Sharan, Jian Peng, Trey Ideker
Nature Cancer 2020

Predicting drug response and synergy using a deep learning model of a cancer cell
Brent Kuenzi, Jisoo Park, Samson H. Fong, Kyle Salinas Sanchez, Jason F. Kreisberg, Jianzhu Ma, Trey Ideker
Cancer Cell 2020

Using deep learning to model the hierarchical structure and function of a cell
Jianzhu Ma, Michael Ku Yu, Samson Fong, Keiichiro Ono, Eric Sage, Barry Demchak, Roded Sharan, Trey Ideker
Nature Methods 2018

A conserved epigenetic progression aligns dog and human age
Tina Wang, Jianzhu Ma, Andrew N. Hogan, Samson Fong, Katherine Licon, Brian Tsui, Jason F. Kreisberg, Peter D. Adams,
Anne-Ruxandra Carvunis, Danika L. Bannasch, Elaine A. Ostrander and Trey Ideker
Cell Systems 2020