About
I am an incoming Research Student at Osaka University (starting June 2026), where I plan to pursue a Ph.D. focused on Generative AI for drug discovery—using generative and foundation models to design molecules and biological sequences. I also maintain broad interests in vision-language models and embodied AI.
Research Motivation
My path to AI research started from a non-traditional background in finance, where I became fascinated by how quantitative models could uncover hidden patterns. This curiosity led me to transition into engineering and eventually into machine learning. During my Master’s at NYU, I worked on multimodal systems—from fine-tuning vision-language models for structured generation to building genomic foundation-model pipelines—and realized that the most exciting applications of generative AI lie at the intersection of computation and the life sciences. I am particularly drawn to the challenge of applying generative models to molecular design and drug discovery, where AI can directly accelerate scientific progress.
Research Interests
- Generative AI for drug discovery—molecular generation, biological sequence design, and foundation models for science (primary direction)
- Vision-language models for structured generation and multimodal reasoning
- Embodied AI and robotics with multimodal grounding
Technical Toolkit
- Programming: Python, TypeScript, Java, MATLAB
- ML / AI: PyTorch, Transformers, multimodal learning
- Tools: Git, Linux, LaTeX, Jupyter
- Languages: English, Chinese (native)
Education
Osaka University
Osaka, Japan — Preparing for Ph.D. in Generative AI for Drug Discovery.
New York University
New York, NY, USA
Beijing Jiaotong University
Beijing, China
Beijing Normal University, Zhuhai
Zhuhai, China