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Abdulai Gassama

@abdulaigassama

I build predictive models for noisy, high-dimensional systems using statistical physics, simulation, and machine learning.

United States

Message

What I'm looking for

I'm looking to apply statistical physics, simulation, optimization, and machine learning to build predictive models for complex systems where data is noisy, high-dimensional, and signal is scarce.

At Brown University, I build large-scale Monte Carlo and parallel tempering simulations for disordered statistical systems, modeling rare events, metastability, and reentrant transitions in noisy high-dimensional settings.

I've developed scaling analyses and RG-based reduced models to identify predictive macroscopic variables, quantified uncertainty in high-variance experimental data, and constructed programmable platforms for analog simulation of optimization-like energy landscapes.

Previously at Syros Pharmaceuticals, I screened compound libraries, automated Python and RDKit cheminformatics pipelines, and developed QSAR-style models to rank drug candidates under sparse, noisy assay data.

I'm also a physics educator and research leader, mentoring machine-learning projects in physics and astronomy and chairing an APS March Meeting focus session on computational methods for statistical mechanics.

Experience

Work history, roles, and key accomplishments

Current

Research Assistant

Current

Brown University

Jan 2022 - Present (4 years 7 months)

Built large-scale Monte Carlo and parallel tempering simulations for disordered statistical systems. Developed scaling analyses and RG-based reduced models to identify predictive macroscopic variables.

Monte Carlo Parallel Tempering Scaling Renormalization Group Uncertainty Quantification Python C++

Teaching Associate

Brown University

Jun 2026 - Aug 2026 (2 months)

Mentored seven student-led machine learning research projects end-to-end, spanning CNN classification, U-Net image reconstruction, autoencoder-based anomaly detection, and LSTM/GRU time-series forecasting. Coached students through core applied-ML failure modes including leakage-safe data partitioning and severe class imbalance.

Machine Learning PyTorch TensorFlow CNN U Net SHAP Mentoring and Coaching

Computational Chemist Intern

Syros Pharmaceuticals

Jan 2022 - Dec 2022 (11 months)

Screened large compound libraries via structure- and ligand-based virtual screening to prioritize candidates for synthesis. Built and automated cheminformatics pipelines to filter, score, and rank molecules by predicted binding affinity and drug-likeness.

Virtual Screening Molecular Docking Python RDKit QSAR Cheminformatics

Independent Research Monograph

Clark University

Jan 2021 - Dec 2021 (11 months)

Authored a 50-page research monograph proving the Riemannian Positive Mass Theorem for graphical manifolds over Euclidean and hyperbolic space in arbitrary dimension. Derived scalar curvature and mass from first principles via tensor calculus.

Differential Geometry Research Writing

Education

Degrees, certifications, and relevant coursework

Brown University

Doctor of Philosophy, Physics

Grade: 4.0/4.0

Doctor of Philosophy in Physics with a GPA of 4.0/4.0, coadvised by Prof. Xinsheng 'Sean' Ling and Prof. J. Michael Kosterlitz.

UQ-Bio Summer School

Summer School, Quantitative Biology

2022 - 2022

Attended several-day modules on single-cell optical microscopy, image processing, multivariable statistics, machine learning, and stochastic simulations of gene regulatory processes.

Clark University

Bachelor of Arts, Physics

2019 - 2022

Bachelor of Arts with Honors in Physics, with a minor in Actuarial and Financial Mathematics. Honors thesis on pattern formation in multicomponent lipid membranes.