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]

  1. Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering
    Kerr Ding, Michael Chin, Yunlong Zhao, Wei Huang, Binh Khanh Mai, Huanan Wang, Peng Liu, Yang Yang, and Yunan Luo
    Nature Communications, 2024
  2. Opportunities and challenges of graph neural networks in electrical engineering
    Eli Chien, Mufei Li, Anthony Aportela, Kerr Ding, Shuyi Jia, Supriyo Maji, Zhongyuan Zhao, Javier Duarte, Victor Fung, Cong Hao, Yunan Luo, Olgica Milenkovic, David Pan, Santiago Segarra, and Pan Li
    Nature Reviews Electrical Engineering, 2024
    PDF
  3. FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames
    Ruidong Wu, Ruihan Guo, Rui Wang, Shitong Luo, Yue Xu, Jiahan Li, Jianzhu Ma, Qiang Liu, Yunan Luo, and Jian Peng
    ICML, 2024 (Spotlight)
    arXiv HTML
  4. Leveraging conformal prediction to annotate enzyme function space with limited false positives
    Kerr Ding, Jiaqi Luo, and Yunan Luo
    PLOS Computational Biology, 2024
  5. Contrastive Fitness Learning: Reprogramming Protein Language Models for Low-N Learning of Protein Fitness Landscape
    Junming Zhao, Chao Zhang, and Yunan Luo
    RECOMB, 2024
    bioRxiv
  6. Calibrated geometric deep learning improves kinase-drug binding predictions
    Yunan Luo, Yang Liu, and Jian Peng
    Nature Machine Intelligence, 2023
    PDF
  7. 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 (Spotlight)
  8. Supervised biological network alignment with graph neural networks
    Kerr Ding, Sheng Wang, and Yunan Luo
    ISMB, 2023
  9. 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
  10. Enzyme function prediction using contrastive learning
    Tianhao Yu, Haiyang Cui, Jianan Li, Yunan Luo, Guangde Jiang, and Huimin Zhao
    Science, 2023
  11. Sensing the shape of functional proteins with topology
    Yunan Luo
    Nature Computational Science, 2023 (News & Views)
    PDF
  12. Interpretable Geometric Deep Learning via Learnable Randomness Injection
    Siqi Miao, Yunan Luo, Mia Liu, and Pan Li
    ICLR, 2023
  13. Contrastive learning of protein representations with graph neural networks for structural and functional annotations
    Jiaqi Luo, and Yunan Luo
    PSB, 2023
  14. 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)
  15. scPretrain: multi-task self-supervised learning for cell-type classification
    Ruiyi Zhang, Yunan Luo, Jianzhu Ma, Ming Zhang, and Sheng Wang
    Bioinformatics, 2022
  16. 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
  17. 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
  18. 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
  19. Crowdsourced mapping of unexplored target space of kinase inhibitors
    Anna Cichońska, and Others (including Yunan Luo in the challenge-winning team)
    Nature Communications, 2021
  20. 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
  21. 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
  22. 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
  23. 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
  24. When causal inference meets deep learning
    Yunan Luo, Jian Peng, and Jianzhu Ma
    Nature Machine Intelligence, 2020 (News & Views)
    PDF
  25. 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
  26. 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
  27. 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
  28. 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
  29. 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)
  30. 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
  31. Metagenomic binning through low-density hashing
    Yunan Luo*, Yun William Yu*, Jianyang Zeng, Bonnie Berger, and Jian Peng
    Bioinformatics, 2018
  32. 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
  33. Deciphering Signaling Specificity with Deep Neural Networks
    Yunan Luo*, Jianzhu Ma*, Yang Liu, Qing Ye, Trey Ideker, and Jian Peng
    RECOMB, 2018
  34. Large-scale integration of heterogeneous pharmacogenomic data for identifying drug mechanism of action
    Yunan Luo, Sheng Wang, Jinfeng Xiao, and Jian Peng
    PSB, 2018
  35. 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)
  36. 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
  37. Low-density locality-sensitive hashing boosts metagenomic binning
    Yunan Luo, Jianyang Zeng, Bonnie Berger, and Jian Peng
    RECOMB, 2016