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Rutgers Biomedical Engineering

Self-driving labs for polymer biomaterials and drug delivery.

We close the loop between robotic synthesis, high-throughput characterization, and machine learning to discover bioactive polymers faster than human-led design.

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How we work

A closed loop, running continuously

We treat discovery as a cycle. Robots make and measure; models learn and decide what to make next — Design, Build, Test, Learn, without waiting on human-led design.

The Design, Build, Test, Learn closed loopA continuous cycle of four stages — Design, Build, Test, and Learn — connected in a ring to represent closed-loop, self-driving experimentation.DesignBuildTestLearn

Research

Three pillars, one method

Method over material: automation and machine learning applied to polymer biomaterials and drug delivery.

01

Automation

Robotic, high-throughput polymer synthesis — including automation-assisted photoinduced ATRP.

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Machine learning

Active learning and Bayesian optimization guide which experiments to run next.

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Self-driving labs

The closed loop applied to nanomedicine and drug delivery.

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Publications

Featured work

  • 2026

    Automation and active learning for the multi-objective optimization of antibody formulations

    Advanced Science

  • 2026

    Automated active learning to optimize hydrogel drug release profiles

    Journal of Controlled Release

  • 2026

    Self-driving lab for the data-driven design of single-chain polymer nanoparticles

    Cell Press Blue

All publications

News

Latest

  • August 1, 2026

    NSF funds a national network of self-driving labs — with Rutgers building the platform

    Rutgers will receive roughly $4.5M of a four-year, $20M NSF award for COAST PCL, a programmable cloud laboratory network for discovering new polymers and soft materials.

  • July 1, 2026

    A new home for the Gormley Lab

    We're rebuilding the lab website around self-driving labs — robotic automation and machine learning for polymer biomaterials and drug delivery.

  • June 5, 2026

    A self-driving lab designs single-chain polymer nanoparticles

    Our self-driving lab closes the loop — designing, making, and testing single-chain polymer nanoparticles with machine learning in the driver's seat.

All news

Open tools

Built in the lab, shared with the field

Software that runs our self-driving experiments.

Geppetto

An autonomous, AI-driven laboratory platform that closes the Design-Build-Test-Learn loop across cloud and bench.

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We're recruiting curious scientists and engineers.

Interested in automation, machine learning, and the future of biomaterials discovery? We'd like to hear from you.

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