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Tianhua Zhai, PhD Image

Tianhua Zhai, PhD

Postdoctoral Researcher;
PennAI Fellow

Tianhua Zhai, PhD Image

Tianhua Zhai, PhD, is a biomedical researcher specializing in AI-driven drug discovery, molecular simulation, and generative protein design. His expertise spans large-scale machine learning, biophysics, medicinal chemistry, and biological mechanism analysis. His work focuses on developing multimodal, generative, and simulation-integrated machine learning models to accelerate the Design–Make–Test–Analyze cycle and enable the discovery of new therapeutics with greater accuracy and efficiency.

Education

  • PhD degree in integrated life sciences, AAIS, Peking university 2026
  • Bachelor degree in statistics, SMS, Peking university 2021

Contact

Email: Tianhua.Zhai@pennmedicine.UPenn.edu
🎓 Google Scholar

Research Highlights

  1. Integrative single-nucleus multi-omics profiling identifies candidate regulators and signaling axes in Alzheimer’s disease lipid-processing microglia. 2026.
  2. Corrigendum to “KEAP1 C151 active site catalysis drives electrophilic signaling to upregulate cytoprotective enzyme expression.” Redox Biology. 2026.
  3. Enhancing BACE1 Inhibitor Discovery with Machine Learning by Integrating Binding Interactions and QSAR Features. Alzheimer’s & Dementia. 2025.
  4. Causal Network of TRIM11: Exploring Druggable Pathways in Alzheimer’s Disease. Alzheimer’s & Dementia. 2025.
  5. Genome-wide association study of ADAS scores identifies novel loci linked to cognitive function in Alzheimer’s disease. Alzheimer’s & Dementia. 2025.
  6. KEAP1 C151 active site catalysis drives electrophilic signaling to upregulate cytoprotective enzyme expression. Redox Biology. 2025.
  7. Catalyzed addition of electrophiles to KEAP1 C151 provides a mechanistic explanation for their pharmacological selectivity for NRF2 activation. Free Radical Biology and Medicine. 2025.
  8. A novel computational analysis integrating social determinants information from EHR and literature with Alzheimer’s disease biological knowledge through large language models and knowledge graphs. Innovation in Aging. 2025.
  9. Leveraging Social Determinants of Health in Alzheimer’s Research Using LLM-Augmented Literature Mining and Knowledge Graphs. AMIA Joint Summits on Translational Science Proceedings. 2025.
  10. Sex-Based Differences in the Association of Epigenetic Age Acceleration with Alzheimer’s Disease Biomarkers and Cognitive Measures. AMIA Joint Summits on Translational Science Proceedings. 2025.
  11. Identifying TRIM11 Upregulators as Therapeutic Targets in Alzheimer’s Disease: A Bayesian Network Approach. AMIA. 2025.
  12. Generating 3D small binding molecules using shape-conditioned diffusion models with guidance. Nature Machine Intelligence. 2025.

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