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Ali Rahnamoun

@alirahnamoun

I build molecular simulation and machine-learning frameworks for force-field development, protein modeling, and drug discovery.

United States

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What I'm looking for

I'm looking to advance molecular modeling and drug discovery through scalable simulation, force-field development, and machine learning, while leading interdisciplinary collaborations and mentoring researchers.

I've developed molecular simulation and force-field technologies at Michigan State University, Attmos Discovery, and CCM Biosciences, including scalable training engines for polarizable force fields and AFFDO, an automated force-field development platform.

My work combines molecular dynamics, QM/MM, reactive simulations, and machine learning to improve protein–ligand modeling, biochemical mechanism studies, and functional protein structure design. I've also built transformer-based protein latent-space models and scalable pipelines for validating ligand–protein binding predictions against high-throughput datasets.

Earlier, at Johns Hopkins and Penn State, I ran large-scale biomolecular simulations, refined CHARMM ionic parameters, developed reactive polymer force fields, and studied graphene defects and polymer degradation. I enjoy leading interdisciplinary work and mentoring researchers in computational techniques.

Experience

Work history, roles, and key accomplishments

Research Faculty

Michigan State University

Jan 2019 - Jan 2026 (7 years)

Developed a fluctuating charge model with scalable training engines for next-generation polarizable force fields. Created hybrid simulation frameworks enabling reactive MD with improved accuracy and transferability.