I am a first-year Ph.D. student in Professor David van Dijk’s lab at Yale University whose work lies at the intersection of large language models, deep learning, and intelligent agent systems. I earned my M.S. from Columbia University and hold a B.Sc. in Statistics from the University of British Columbia (Canada), with a strong foundation in data-driven discovery.
My research focuses on developing foundation models and AI agents to tackle complex biological challenges. I am passionate about applying these approaches to biological data while collaborating across disciplines to push the boundaries of AI in biology.
I am always interested in discussing new ideas and potential collaborations. Feel free to reach out via email!
🔥 News
- 2024.09: 🎉🎉 Started my Ph.D. journey at Yale University in Professor David van Dijk’s lab!
- 2024.05: 🎉🎉 Graduated with M.S. from Columbia University.
📖 Education
- 2024.09 - Present, Ph.D. in Computer Science, Yale University, New Haven, CT
- Advisor: Professor David van Dijk
- Research focus: Large language models, deep learning, and AI agents for biological discovery
- 2022 - 2024, M.S. in Computer Science, Columbia University, New York, NY
- 2018 - 2022, B.Sc. in Statistics, University of British Columbia, Vancouver, Canada
🌟 Selected Publications
Intelligence at the Edge of Chaos
Shiyang Zhang, Aakash Patel, Syed A Rizvi, Nianchen Liu, Sizhuang He, Amin Karbasi, Emanuele Zappala, David van Dijk
arXiv preprint, 2024 | Paper
A novel framework exploring the intersection of complexity theory and neural network dynamics.
Scaling Large Language Models for Next-Generation Single-Cell Analysis
Syed Asad Rizvi*, Daniel Levine*, Aakash Patel*, Shiyang Zhang, Eric Wang, Sizhuang He, David Zhang, et al.
bioRxiv, 2025 | Paper
Developing foundation models specifically designed for single-cell genomics data analysis.
RankAdaptor: Hierarchical Dynamic Low-Rank Adaptation for Structural Pruned LLMs
Changhai Zhou, Shijie Han, Shiyang Zhang, Shichao Weng, Zekai Liu, Cheng Jin
arXiv preprint, 2024 | Paper
Novel approach for efficient fine-tuning of large language models through dynamic rank adaptation.
🎖 Honors and Awards
Updates coming soon!
💬 Talks & Presentations
Coming soon!
💻 Experience
Updates coming soon!
📝 All Publications
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