Yurui Li
Ph.D. Student in Informatics · University of Illinois Urbana-Champaign · DREAM Lab
I am a Ph.D. student in Informatics at the University of Illinois Urbana-Champaign, advised by Prof. Haohan Wang. My research focuses on developing computational methods based on deep learning and large language models to study cellular interactions, regulatory processes, and the biological mechanisms underlying them.
I aim to advance AI-driven approaches that enable deeper insights into complex cellular systems and facilitate biological discovery.
- yuruil2 [at] illinois.edu
- Google Scholar
- GitHub
Research
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Context-aware gene regulatory mechanism discovery with LLMs
An LLM-based framework that identifies context-dependent gene regulatory mechanisms by combining a biological knowledge graph of experimentally supported interactions with context-specific molecular evidence, using evidence-guided reasoning.
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AI virtual cells and spatial perturbation modeling
A review of mathematical and AI-based virtual cell models, and a probabilistic spatial perturbation framework that predicts how perturbing a cell affects its neighbors, accounting for cellular heterogeneity and the local microenvironment.
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Cell–cell communication and cell-specific gene regulation (HEISN)
A hierarchical graph neural network that jointly infers intercellular signaling and cell-specific gene regulatory networks from spatial transcriptomics, applied to oral squamous cell carcinoma and Alzheimer's disease data.
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Spatially varying gene regulatory networks (SVGRN)
A two-stage deep learning framework combining structural equation modeling with conditional variational autoencoders to infer cell- and spot-specific gene regulatory networks that vary with spatial context.
Selected Publications
- Spatially varying gene regulation network inference from spatial transcriptomics Bioinformatics Advances, 6(1), vbag230, 2026 · Oral presentation at ISMB 2026 DOI
- Inferring spatially varying intercellular and intracellular signaling via hierarchical graph neural networks Under review at npj Systems Biology and Applications, 2026
- Joint modeling of multi-timepoint spatial observations for time-resolved spatial-unit-specific gene regulatory network inference bioRxiv, 2026 bioRxiv
- DiffSim: Aligning Diffusion Model and Molecular Dynamics Simulation for Blind Docking IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024 DOI
Full list on Google Scholar.
Experience
- Natera May 2025 – Aug 2025 Bioinformatics Scientist Intern
- Agency for Science, Technology and Research (A*STAR) Mar 2023 – Aug 2023 Research Intern
- SenseTime Jan 2022 – May 2022 Intern, Autonomous Driving Prediction Algorithm
Education
- University of Illinois Urbana-Champaign 2023 – present Ph.D. in Informatics
- National University of Singapore 2022 – 2023 Master of Technology in Intelligent Systems
- Northeastern University, China 2018 – 2022 B.Eng. in Computer Science and Technology