Research

My research focuses on developing innovative polymer-based solutions for protein stabilization, combining experimental approaches with machine learning to advance biomaterial design.

Overview

Research Interests

Polymer Chemistry

Synthesis and characterization of random copolymers for biomedical applications

Protein Stabilization

Developing polymer-enzyme hybrids for enhanced biocatalysis

Machine Learning

Data-driven approaches for biomaterial complexity mapping

High-Throughput Screening

Automated methodologies using liquid handling robots

Current Project • 2022-2026

Random Copolymers for Protein Stabilization

My doctoral research investigates polymer-enzyme hybrids in water-miscible organic solvents using high-throughput approaches. This work aims to develop next-generation biocatalysts with enhanced stability and activity.

Research Objectives

  • Develop automated methodologies for evaluating protein stabilization
  • Investigate polymer-enzyme interactions in organic solvent systems
  • Apply machine learning for predictive modeling of polymer performance
  • Create high-throughput screening platforms using liquid handling robots
Polymer Synthesis Enzyme Assays SAXS Analysis Automation Machine Learning

Lab Affiliation: Dr. Adam Gormley Laboratory

Institution: Rutgers University, Department of Biomedical Engineering

Random Copolymers Research - High-throughput polymer characterization

Recent Presentations

BMES Conference 2025

San Diego, CA • October 2025

BESS Symposium

Rutgers University • December 2024

Computational Research

Machine Learning in Biomaterials

Applying data-driven approaches to understand and predict the complex relationships between polymer structure, composition, and biological function. This work has resulted in a first-author publication in Tissue Engineering Part A.

Key Contributions

  • Developed ML models for mapping biomaterial complexity
  • Created predictive frameworks for polymer-protein interactions
  • Automated data analysis pipelines for high-throughput experiments
  • Integrated SAXS analysis with machine learning for structural discovery
Python Scikit-learn Data Visualization SAXS Analysis
View Related Publications
Machine Learning Research - Data visualization and analysis
Undergraduate Research

Past Projects

2017-2018 Honourable Mention

Tension-Induced Rupture of Lipid Membranes

Dr. Alexander Neimark Laboratory • Rutgers University

Investigated the mechanical properties of lipid membranes under tension using computational methodologies. This research explored the fundamental biophysics of membrane rupture and stability.

Methods & Tools

Computational Modeling Molecular Dynamics Biophysics

Presentations

  • • Gulf Coast Undergraduate Research Symposium, Rice University (Oct 2018)
  • • Aresty Undergraduate Research Symposium, Rutgers (April 2018)
2018

Polymer Characterization Studies

Dr. Adam Gormley Laboratory • Rutgers University

Conducted foundational research on polymer-based biomaterial systems, including vacuum filtration techniques and solubility characterization studies. This early work laid the groundwork for my doctoral research.

Methods & Tools

Vacuum Filtration Solubility Analysis Polymer Synthesis

Key Learnings

  • • Polymer synthesis and purification techniques
  • • Biomaterial characterization methodologies
Expertise

Methods & Techniques

Laboratory Techniques

Polymer Synthesis Vacuum Filtration Solubility Analysis Enzyme Assays Gold Nanoparticle Diagnostics High-Throughput Screening

Analytical Methods

SAXS Analysis Polymer Characterization Spectroscopy Chromatography Nanotechnology

Computational Tools

Machine Learning Python Data Visualization Statistical Analysis Automated Experiment Design

Automation

Liquid Handling Robots Automated Assays photoATRP Automation SAXS Assistant

Interested in Collaboration?

I'm always open to discussing research collaborations, especially in polymer chemistry, protein engineering, and machine learning applications.

Get in Touch View Publications