Yichen Zhang · Researcher
Building generative systems for scientific discovery.
Research Student at Osaka University, working toward generative and foundation-model approaches for molecules and biological sequences.
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Research
Questions I care about
Generative AI for Drug Discovery
How can generative models navigate molecular and biological design spaces while respecting scientific constraints?
Multimodal Intelligence
How can models connect visual evidence, language, and structured outputs with dependable reasoning?
Embodied AI & Robotics
How can agents ground perception and language in actions that remain robust outside curated environments?
VLM Fine-tuning for Schema-Constrained Food Extraction
2025Fine-tuned SmolVLM2-500M for reliable JSON extraction from food images and released reproducible weights for downstream integration.
GeneLM-Evo2: Zero-shot Genomic Variant Pathogenicity Analysis
2025Built a zero-shot pathogenicity scoring pipeline around Evo2 7B with long-context genomic inference and a scalable GPU serving stack.
Efficiency Analysis of Tiny Recursive Models for Reasoning
2025Reproduced Tiny Recursive Models and measured how accuracy, throughput, and compute budgets interact on Sudoku-Extreme reasoning tasks.
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Updates
Recent notes
- Joined Osaka University as a Research Student, preparing for Ph.D. study in generative AI for drug discovery.
- Completed an M.S. in Computer Engineering at New York University.
- Open-sourced GeneLM-Evo2 and a schema-constrained VLM fine-tuning pipeline.
Collaboration
Interested in generative models for science?
I am open to research conversations, collaborations, and thoughtful exchanges across AI and the life sciences.
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