4 citations · 9 across the 4 of their papers we have counts for
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cs.SE2025★ 4 cited
Accelerating Drug Discovery Through Agentic AI: A Multi-Agent Approach to Laboratory Automation in the DMTA Cycle
Yao Fehlis, Charles Crain, Aidan Jensen +9
The pharmaceutical industry faces unprecedented challenges in drug discovery, with traditional approaches struggling to meet modern therapeutic development demands. This paper intr…
cs.SE2025★ 4 cited
Accelerating drug discovery with Artificial: a whole-lab orchestration and scheduling system for self-driving labs
Yao Fehlis, Paul Mandel, Charles Crain +2
Self-driving labs are transforming drug discovery by enabling automated, AI-guided experimentation, but they face challenges in orchestrating complex workflows, integrating diverse…