Lianghong Chen — accepted AI-conference papers

2026

MAC-AMP: A Closed-Loop Multi-Agent Collaboration System for Multi-Objective Antimicrobial Peptide Design

Gen Zhou, Sugitha Janarthanan, Lianghong Chen, Pingzhao Hu

ICLR 2026poster

To address the global health threat of antimicrobial resistance, antimicrobial peptides (AMP) are being explored for their potent and promising ability to fight resistant pathogens. While artificial intelligence (AI) is being employed to advance AMP discovery and design, most AMP design models strug…

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2025

Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design

Lianghong Chen, Dongkyu Eugene Kim, Mike Domaratzki, Pingzhao Hu

NeurIPS 2025poster

Designing de novo 3D molecules with desirable properties remains a fundamental challenge in drug discovery and molecular engineering. While diffusion models have demonstrated remarkable capabilities in generating high-quality 3D molecular structures, they often struggle to effectively control comple…

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