3 papers
cs.AI2026
A Modular Agentic Framework for Synthetically Constrained Multi-Objective Hit-to-Lead Optimization
Kelvin P. Idanwekhai, Enes Kelestemur, Benjamin Strickland +6
Hit-to-lead optimization requires iterative design of hit analogs across competing potency, selectivity, physicochemical, pharmacokinetic, safety, and synthetic constraints. We pre…
cs.AI2026
From Prompts to Protocols: An AI Agent for Laboratory Automation
Angelos Angelopoulos, James F. Cahoon, Ron Alterovitz
Automating science laboratories enables faster, safer, more accurate, and more reproducible execution of protocols, accelerating the discovery and testing of new materials, drugs,…
cs.AI2025
Generalizing Multi-Objective Search via Objective-Aggregation Functions
Hadar Peer, Eyal Weiss, Ron Alterovitz +1
Multi-objective search (MOS) has become essential in robotics, as real-world robotic systems need to simultaneously balance multiple, often conflicting objectives. Recent works exp…