Selected research
My research connects reliable multi-agent systems with an earlier body of work in materials and molecular discovery, multimodal biodiversity, and scientific machine learning.
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Research portfolio
Measuring Multi-Agent Scientific Reasoning
Open, schema-stable resources for studying how AI agents collaborate on scientific problems—from protocol choice and cost to critique uptake, trajectory value, and agent attribution.
Research portfolio
Generative and multi-fidelity scientific AI
My Ph.D. work connected generative modeling, molecular language models, reinforcement learning, and multi-fidelity learning to materials and molecular design—from photovoltaic microstructures to organic chemical space.
AI-ready biodiversity at scale
A NeurIPS 2024 Spotlight project presenting 161.9 million research-grade images across approximately 366,600 species, along with 40 million captioned training examples, multimodal models, and biodiversity benchmarks.
Visiting Scientist at Corteva Agriscience
Applied RLHF with preference-based insights for domain-specific model customization. Additional technical details will be added after public wording is confirmed.
AI Resident at X, Google LLC
Developed multi-agent collaboration frameworks using a Mixture-of-Experts architecture with multimodal data streams. More project detail will be added after public wording is confirmed.