Fangping Wan<br>(万 方平) 😄

Fangping Wan
(万 方平)

(he/him)

Computational Scientist

University of Pennsylvania

Career Overview

Fangping Wan is a computational scientist in the Machine Biology Group led by Dr. César de la Fuente at the University of Pennsylvania. His research lies broadly in the area of AI for Science, with a focus on applying advanced machine learning approaches to challenges in biomolecular modeling and drug discovery. He integrates large language models, graph neural networks, and generative AI frameworks to model protein sequences, molecular structures, and biological interactions. By combining predictive analysis with generative design, his work explores new ways to understand molecular function and to accelerate the identification of promising therapeutic candidates. Positioned at the intersection of computational biology, artificial intelligence, and biomedical engineering, his research brings together method development and domain exploration, contributing to a broader view of how AI can support advances in biology and chemistry.

Experience

August 2024 – Present

Supervisor: Dr. César de la Fuente

August 2021 – August 2024

Supervisor: Dr. César de la Fuente

Machine Learning Engineer

Silexon AI Technology, Beijing, China

July 2020 – July 2021

Education

PhD in Computer Science

Tsinghua University, Beijing, China

September 2015 – June 2020

Supervisor: Dr. Jianyang Zeng

BS in Computer Science

Tianjin University, Tianjin, China

September 2011 – June 2015

Interests

AI4Science Deep Learning Generative AI Large Language Model Graph Neural Network Drug Discovery Computational Biology
Publications
Marcelo D. T. Torres , Leo Tianlai Chen , Fangping Wan , Pranam Chatterjee , Cesar de la Fuente-Nunez
Marcelo D. T. Torres* , Fangping Wan* , Cesar de la Fuente
Natalie Maus , Kyurae Kim , Yimeng Zeng , Haydn Thomas Jones , Fangping Wan , Marcelo D. T. Torres , Cesar de la Fuente-Nunez , Jacob R. Gardner.

Predicting and generating antibiotics against future pathogens with ApexOracle

NeurIPS 2025 2nd Workshop FM4LS, 2025 (Journal version in preparation)
Tianang Leng* , Fangping Wan* , Marcelo D. T. Torres , Cesar de la Fuente-Nunez
Yimeng Zeng , Natalie Maus , Haydn Thomas Jones , Jeffrey Tao , Fangping Wan , Marcelo D. T. Torres , Cesar de la Fuente-Nunez , Ryan Marcus , Osbert Bastani , Jacob R. Gardner
Angela Cesaro* , Fangping Wan* , Haoyuan Shi* , Kaiyang Wang , C Mark Maupin , Matt L Barker , Jiqian Liu , Stephen J Fox , Jingjie Yeo , Cesar de la Fuente-Nunez
Fangping Wan* , Marcelo D. T. Torres* , Changge Guan , Cesar de la Fuente-Nunez
Changge Guan* , Fangping Wan* , Marcelo D. T. Torres , Cesar de la Fuente-Nunez
Angela Cesaro , Fangping Wan , Marcelo D. T. Torres , Cesar de la Fuente-Nunez
Marcelo D. T. Torres* , Yimeng Zeng* , Fangping Wan* , Natalie Maus , Jacob R. Gardner , Cesar de la Fuente-Nunez

Analyzing Large-Scale Single-Cell RNA-Seq Data Using Coreset

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2024
Khalid Usman , Fangping Wan , Dan Zhao , Jian Peng , Jianyang Zeng
Fangping Wan* , Marcelo D. T. Torres* , Jacqueline Peng , Cesar de la Fuente
Fangping Wan* , Felix Wong* , James J. Collins , Cesar de la Fuente

Deep learning tools to accelerate antibiotic discovery

Expert Opinion on Drug Discovery, 2023
Angela Cesaro , Mojtaba Bagheri , Marcelo D. T. Torres , Fangping Wan , Cesar de la Fuente-Nunez
Han Li , Xinyi Zhao , Shuya Li , Fangping Wan , Dan Zhao , Jianyang Zeng
Fangping Wan* , Daphne Kontogiorgos-Heintz* , Cesar de la Fuente-Nunez
Eugene F Douglass Jr. , Robert J Allaway , Bence Szalai , Wenyu Wang , Tingzhong Tian , Adria Fernandez-Torras , Ron Realubit , Charles Karan , Shuyu Zheng , Alberto Pessia , Ziaurrehman Tanoli , Mohieddin Jafari , Fangping Wan , Shuya Li , Yuanpeng Xiong , Miquel Duran-Frigola , Martino Bertoni , Pau Badia-i-Mompel , Lidia Mateo , Oriol Guitart-Pla , Verena Chung , Jing Tang , Jianyang Zeng , Patrick Aloy , Julio Saez-Rodriguez , Justin Guinney , Daniela S Gerhard , Andrea Califano
Yipin Lei , Shuya Li , Ziyi Liu , Fangping Wan , Tingzhong Tian , Shao Li , Dan Zhao , Jianyang Zeng
Adi L. Tarca , Bálint Ármin Pataki , Roberto Romero , Marina Sirota , Yuanfang Guan , Rintu Kutum , Nardhy Gomez-Lopez , Bogdan Done , Gaurav Bhatti , Thomas Yu , Gaia Andreoletti , Tinnakorn Chaiworapongsa , The DREAM Preterm Birth Prediction Challenge Consortium , Sonia S. Hassan , Chaur-Dong Hsu , Nima Aghaeepour , Gustavo Stolovitzky , Istvan Csabai , James C. Costello
Anna Cichonska , Balaguru Ravikumar , Robert J Allaway , Sungjoon Park , Fangping Wan , Olexandr Isayev , Shuya Li , Michael J Mason , Andrew Lamb , Minji Jeon , Sunkyu Kim , Mariya Popova , Jianyang Zeng , Kristen Dang , Gregory Koytiger , Jaewoo Kang , Carrow I Wells , Timothy M Willson , Tudor I Oprea , Avner Schlessinger , David H Drewry , Gustavo A Stolovitzky , Krister Wennerberg , Justin Guinney , Tero Aittokallio
Yiyue Ge* , Tingzhong Tian* , Sulin Huang* , Fangping Wan* , Jingxin Li , Shuya Li , Hui Yang , Lixiang Hong , Nian Wu , Enming Yuan , Lili Cheng , Yipin Lei , Hantao Shu , Xiaolong Feng , Ziyuan Jiang , Ying Chi , Xiling Guo , Lunbiao Cui , Liang Xiao , Zeng Li , Chunhao Yang , Zehong Miao , Haidong Tang , Ligong Chen , Hainian Zeng , Dan Zhao , Fengcai Zhu , Xiaokun Shen , Jianyang Zeng

A novel machine learning based framework for modeling transcription elongation

Proceedings of the National Academy of Sciences (PNAS), 2021
Peiyuan Feng , An Xiao , Meng Fang , Fangping Wan , Shuya Li , Peng Lang , Dan Zhao , and Jianyang Zeng
Han Li , Xinyi Zhao , Shuya Li , Fangping Wan , Dan Zhao , and Jianyang Zeng
Lixiang Hong , Jinjian Lin , Shuya Li , Fangping Wan , Hui Yang , Tao Jiang , Dan Zhao , Jianyang Zeng
Rong Ma , Yi Li , Chenxing Li , Fangping Wan , Hailin Hu , Wei Xu , Jianyang Zeng
Shuya Li* , Fangping Wan* , Hantao Shu , Tao Jiang , Dan Zhao , Jianyang Zeng
Fangping Wan* , Shuya Li* , Tingzhong Tian , Yipin Lei , Dan Zhao , Jianyang Zeng
Yan Hu , Ziqiang Wang , Hailin Hu , Fangping Wan , Lin Chen , Yuanpeng Xiong , Xiaoxia Wang , Dan Zhao , Weiren Huang , Jianyang Zeng
Fangping Wan* , Yue Zhu* , Hailin Hu* , Antao Dai , Xiaoqing Cai , Ligong Chen , Haipeng Gong , Tian Xia , Dehua Yang , Ming-Wei Wang , Jianyang Zeng
Fangping Wan , Lixiang Hong , An Xiao , Tao Jiang , Jianyang Zeng