Guangyuan Li

Research Interests:

I have dual training in computational biology and translational cancer immunology, with a focus on developing novel algorithms and analytical pipelines that integrate machine learning, probabilistic modeling, and statistical methods. My work has resulted in widely adopted software tools, algorithms, and databases in the field. On the translational side, my research has contributed to the discovery of several clinically actionable tumor antigens, some of which are currently undergoing preclinical evaluation with therapeutic modalities such as CAR-T cells, BiTEs, and ADCs. My long-term goal is to merge computational innovation with a deep commitment to cancer biology to accelerate therapeutic discovery and advance precision medicine.

Biography:

• Assistant Professor of Practice, University of Notre Dame, 2026-present
• Postdoctoral Fellow, New York University, 2023-2026
• Ph.D. Biomedical Informatics, University of Cincinnati, United States, 2023
• B.S. Biology, Wuhan University, China, 2019

Selected Papers:

• Guangyuan Li* , Omar Uriel Guzman-Bringas, Aman Sharma, Maxence Dellacherie, Palak Sekhri, Rachel Yamin, Dejan Stepec, Maximilien Burq, Ioana Clotea, Ethan Tardio, Aswin Natarajan, Zachary Harpaz, Xinya Liu, David Requena, Darren Taylor, Beatrix Ueberheide, Michelle Krogsgaard, Conrad Russell Cruz, Peter Cimermancic, Mark Yarmarkovich “A pan-cancer atlas of therapeutic T cell targets”, BioRxiv. 2025. https://www.biorxiv.org/content/10.1101/2025.01.22.634237v2.
• Guangyuan Li*, Shweta Mahajan*, Siyuan Ma, Erin D. Jeffery, Xuan Zhang, Anukana Bhattacharjee, Meenakshi Venkatashubramanian et al. “Splicing Neoantigen Discovery with SNAF Reveals Shared Targets for Cancer Immunotherapy.” Science Translational Medicine. 2024. https://doi.org/10.1126/scitranslmed.ade2886.
• Guangyuan Li*, Baobao Song, Harinder Singh, V.B. Surya Prasath, H. Leighton Grimes, Nathan Salomonis. “Decision level integration of unimodal and multimodal single cell data with scTriangulate” Nature Communications. 2023. https://doi.org/10.1038/s41467-023-36016-y.
• Guangyuan Li*, Daniel Schnell, Anukana Bhattacharjee, Mark Yarmarkovich, Nathan Salomonis. “Quantifying tumor specificity using Bayesian probabilistic modeling for drug and immunotherapeutic target discovery.” Cell Reports Methods. 2024. https://doi.org/10.1016/j.crmeth.2024.100900.
• Guangyuan Li*, Balaji Iyer, V.B. Surya Prasath, YiZhao Ni, Nathan Salomonis. “DeepImmuno: Deep Learning-Empowered Prediction and Generation of Immunogenic Peptides for T-Cell Immunity.” Briefings in Bioinformatics. 2021. https://doi.org/10.1093/bib/bbab160.
• Zhang Xuan, Baobao Song, Maximillian J. Carlino, Guangyuan Li, Kyle Ferchen, Mi Chen, Evrett N. Thompson, et al. “An Immunophenotype-Coupled Transcriptomic Atlas of Human Hematopoietic Progenitors.” Nature Immunology. 2024. https://www.nature.com/articles/s41590-024-01782-4.

To read more publications: Click here.

Primary Teaching Areas:

• Introduction to Computational Genomics
  Applied Machine Learning in Biomedicine