Yunan Luo

Assistant Professor
Computational Science and Engineering
Georgia Institute of Technology

Email: yunan [at] gatech.edu
Office: CODA S1245
Address: 756 W Peachtree St NW, Atlanta, GA 30308

I am an Assistant Professor in the School of Computational Science and Engineering (CSE), Georgia Institute of Technology since January 2022. I received my PhD in 2021 from the Department of Computer Science at the University of Illinois Urbana-Champaign, advised by Prof. Jian Peng. Prior to that, I received my bachelor’s degree in Computer Science from Yao Class at Tsinghua University in 2016.

I am broadly interested in computational biology and machine learning, with a focus on developing AI and data science methods to reveal core scientific insights into biology and medicine. Recent interests include machine learning, geometric deep learning, generative models, network and system biology, functional genomics, cancer genomics, drug repositioning and discovery, and AI-guided protein engineering.

Recent News

Selected Awards

  • NIH Maximizing Investigators’ Research Award (MIRA) (R35 for ESI), 2023
  • Top-10 Reviewer Award, LOG Conference, 2023
  • Amazon Research Award, 2022
  • Top-20 Reviewer Award, LOG Conference, 2022

Teaching

Papers

[Google Scholar]

(*=equal contribution)

  1. Contrastive Fitness Learning: Reprogramming Protein Language Models for Low-N Learning of Protein Fitness Landscape
    Junming Zhao, Chao Zhang, and Yunan Luo
    RECOMB, 2024 (accepted)
  2. Calibrated geometric deep learning improves kinase-drug binding predictions
    Yunan Luo, Yang Liu, and Jian Peng
    Nature Machine Intelligence, 2023
  3. LinkerNet: Fragment Poses and Linker Co-Design with 3D Equivariant Diffusion
    Jiaqi Guan, Xingang Peng, PeiQi Jiang, Yunan Luo, Jian Peng, and Jianzhu Ma
    NeurIPS, 2023
  4. Supervised biological network alignment with graph neural networks
    Kerr Ding, Sheng Wang, and Yunan Luo
    ISMB, 2023
  5. Metabolic activity organizes olfactory representations
    Wesley W Qian, Jennifer N Wei, Benjamin Sanchez-Lengeling, Brian K Lee, Yunan Luo, Marnix Vlot, Koen Dechering, Jian Peng, Richard C Gerkin, and Alexander B Wiltschko
    eLife, 2023
  6. Enzyme function prediction using contrastive learning
    Tianhao Yu, Haiyang Cui, Jianan Li, Yunan Luo, Guangde Jiang, and Huimin Zhao
    Science, 2023
  7. Sensing the shape of functional proteins with topology
    Yunan Luo
    Nature Computational Science, 2023 (News & Views)
  8. Interpretable Geometric Deep Learning via Learnable Randomness Injection
    Siqi Miao, Yunan Luo, Mia Liu, and Pan Li
    ICLR, 2023
  9. Contrastive learning of protein representations with graph neural networks for structural and functional annotations
    Jiaqi Luo, and Yunan Luo
    PSB, 2023
  10. Next Decade’s AI-Based Drug Development Features Tight Integration of Data and Computation
    Yunan Luo, Jian Peng, and Jianzhu Ma
    Health Data Science, 2022 (Perspective)
  11. scPretrain: multi-task self-supervised learning for cell-type classification
    Ruiyi Zhang, Yunan Luo, Jianzhu Ma, Ming Zhang, and Sheng Wang
    Bioinformatics, 2022
  12. ECNet is an evolutionary context-integrated deep learning framework for protein engineering
    Yunan Luo*, Guangde Jiang*, Tianhao Yu, Yang Liu, Lam Vo, Hantian Ding, Yufeng Su, Wesley Wei Qian, Huimin Zhao, and Jian Peng
    Nature Communications, 2021
  13. Deep geometric representations for modeling effects of mutations on protein-protein binding affinity
    Xianggen Liu, Yunan Luo, Pengyong Li, Sen Song, and Jian Peng
    PLoS computational biology, 2021
  14. Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients
    Jianzhu Ma, Samson H. Fong, Yunan Luo, Christopher J. Bakkenist, John Paul Shen, Soufiane Mourragui, Lodewyk F. A. Wessels, Marc Hafner, Roded Sharan, Jian Peng, and Trey Ideker
    Nature Cancer, 2021
  15. Crowdsourced mapping of unexplored target space of kinase inhibitors
    Anna Cichońska, and Others (including Yunan Luo in the challenge-winning team)
    Nature Communications, 2021
  16. An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19
    Yiyue Ge, Tingzhong Tian, Suling Huang, Fangping Wan, Jingxin Li, Shuya Li, Xiaoting Wang, Hui Yang, Lixiang Hong, Nian Wu, Enming Yuan, Yunan Luo, Lili Cheng, Chengliang Hu, Yipin Lei, Hantao Shu, Xiaolong Feng, Ziyuan Jiang, Yunfu Wu, Ying Chi, Xiling Guo, Lunbiao Cui, Liang Xiao, Zeng Li, Chunhao Yang, Zehong Miao, Ligong Chen, Haitao Li, Hainian Zeng, Dan Zhao, Fengcai Zhu, Xiaokun Shen, and Jianyang Zeng
    Signal Transduction and Targeted Therapy, 2021
  17. Evolutionary context-integrated deep sequence modeling for protein engineering
    Yunan Luo, Lam Vo, Hantian Ding, Yufeng Su, Yang Liu, Wesley Wei Qian, Huimin Zhao, and Jian Peng
    RECOMB, 2020
  18. Characterization of SARS-CoV-2 viral diversity within and across hosts
    Palash Sashittal*, Yunan Luo*, Jian Peng, and Mohammed El-Kebir
    bioRxiv:2020.05.07.083410, 2020
  19. STAIR 2.0: A Generic and Automatic Algorithm to Fuse Modis, Landsat, and Sentinel-2 to Generate 10 m, Daily, and Cloud-/Gap-Free Surface Reflectance Product
    Yunan Luo, Kaiyu Guan, Jian Peng, Sibo Wang, and Yizhi Huang
    Remote Sensing, 2020
  20. When causal inference meets deep learning
    Yunan Luo, Jian Peng, and Jianzhu Ma
    Nature Machine Intelligence, 2020 (News & Views)
  21. Deriving high-spatiotemporal-resolution leaf area index for agroecosystems in the U.S. Corn Belt using Planet Labs CubeSat and STAIR fusion data
    Hyungsuk Kimm, Kaiyu Guan, Chongya Jiang, Bin Peng, Laura F. Gentry, Scott C. Wilkin, Sibo Wang, Yaping Cai, Carl J. Bernacchi, Jian Peng, and Yunan Luo
    Remote Sensing of Environment, 2020
  22. Integrating Deep Neural Networks and Symbolic Inference for Organic Reactivity Prediction
    Wesley Wei Qian, Nathan T. Russell, Claire L. W. Simons, Yunan Luo, Martin D. Burke, and Jian Peng
    chemRxiv:11659563, 2020
  23. Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
    Yang Liu, Yunan Luo, Yuanyi Zhong, X. Chen, Qiang Liu, and Jian Peng
    arXiv:1905.13420, 2019
  24. DeepMask: An algorithm for cloud and cloud shadow detection in optical satellite remote sensing images using deep residual network
    Ke Xu, Kaiyu Guan, Jian Peng, Yunan Luo, and Sibo Wang
    arXiv:1911.03607, 2019
  25. Integrating thermodynamic and sequence contexts improves protein-RNA binding prediction
    Yufeng Su*, Yunan Luo*, Xiaoming Zhao, Yang Liu, and Jian Peng
    PLoS computational biology, 2019 (Presented at GLBIO’19)
  26. Mitigating Data Scarcity in Protein Binding Prediction Using Meta-Learning
    Yunan Luo*, Jianzhu Ma*, Xiaoming Zhao, Yufeng Su, Yang Liu, Trey Ideker, and Jian Peng
    RECOMB, 2019
  27. Metagenomic binning through low-density hashing
    Yunan Luo*, Yun William Yu*, Jianyang Zeng, Bonnie Berger, and Jian Peng
    Bioinformatics, 2018
  28. STAIR: A generic and fully-automated method to fuse multiple sources of optical satellite data to generate a high-resolution, daily and cloud-/gap-free surface reflectance product
    Yunan Luo, Kaiyu Guan, and Jian Peng
    Remote Sensing of Environment, 2018
  29. Deciphering Signaling Specificity with Deep Neural Networks
    Yunan Luo*, Jianzhu Ma*, Yang Liu, Qing Ye, Trey Ideker, and Jian Peng
    RECOMB, 2018
  30. Large-scale integration of heterogeneous pharmacogenomic data for identifying drug mechanism of action
    Yunan Luo, Sheng Wang, Jinfeng Xiao, and Jian Peng
    PSB, 2018
  31. A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information
    Yunan Luo*, Xinbin Zhao*, Jingtian Zhou*, Jinglin Yang, Yanqing Zhang, Wenhua Kuang, Jian Peng, Ligong Chen, and Jianyang Zeng
    Nature communications, 2017 (Extended version of the RECOMB’17 paper)
  32. A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information
    Yunan Luo*, Xinbin Zhao*, Jingtian Zhou*, Jinglin Yang, Yanqing Zhang, Wenhua Kuang, Jian Peng, Ligong Chen, and Jianyang Zeng
    RECOMB, 2017
  33. Low-density locality-sensitive hashing boosts metagenomic binning
    Yunan Luo, Jianyang Zeng, Bonnie Berger, and Jian Peng
    RECOMB, 2016