Barnabas Poczos

Autonomous Discovery of Battery Electrolytes with Robotic Experimentation and Machine Learning

Cell Reports Physical Science · 2020 · 163 citations

Innovations in batteries can require years of experimentation for design and optimization. We report an autonomous approach to the optimization of a battery electrolyte that uses machine learning coupled to a robotic test-stand to perform hundreds of sequential experiments. We search for mixtures of salts in aqueous electrolytes with high electrochemical stability using Bayesian optimization. In 40 hours of experimentation testing for 140 electrolyte formulas, we converge on a non-intuitive opti…

Hierarchical Machine Learning for High-Fidelity 3D Printed Biopolymers

ACS Biomaterials Science & Engineering · 2020 · 106 citations

= 0.643). Optimization allowed for the prediction of build parameters that gave rise to high-fidelity prints of the measured features. A trade-off was identified when optimizing for the fidelity of different features printed within the same construct, showing the need for complex predictive design tools. A combination of known and discovered relationships was used to generate process maps for the 3D bioprinting designer that show error minimums based on the chosen input variables. Our approach o…

Diffusion Models in De Novo Drug Design

Journal of Chemical Information and Modeling · 2024-09-25 · 72 citations

Diffusion models have emerged as powerful tools for molecular generation, particularly in the context of 3D molecular structures. Inspired by nonequilibrium statistical physics, these models can generate 3D molecular structures with specific properties or requirements crucial to drug discovery. Diffusion models were particularly successful at learning the complex probability distributions of 3D molecular geometries and their corresponding chemical and physical properties through forward and reve…

SenSet, a novel human lung senescence cell gene signature, identifies cell-specific senescence mechanisms

bioRxiv (Cold Spring Harbor Laboratory) · 2024-12-22 · 7 citations

Cellular senescence is a major hallmark of aging. Senescence is defined as an irreversible growth arrest observed when cells are exposed to a variety of stressors including DNA damage, oxidative stress, or nutrient deprivation. While senescence is a well-established driver of aging and age-related diseases, it is a highly heterogeneous process with significant variations across organisms, tissues, and cell types. The relatively low abundance of senescence in healthy aged tissues represents a maj…

Learning from B Cell Evolution: Adaptive Multi-Expert Diffusion for Antibody Design via Online Optimization

bioRxiv (Cold Spring Harbor Laboratory) · 2025-08-03 · 3 citations

Abstract Recent advances in diffusion models have shown remarkable potential for antibody design, yet existing approaches apply uniform generation strategies that cannot adapt to each antigen’s unique requirements. Inspired by B cell affinity maturation—where antibodies evolve through multi-objective optimization balancing affinity, stability, and self-avoidance—we propose the first biologically-motivated framework that leverages physics-based domain knowledge within an online meta-learning syst…