Randy F. Espinal

WORK HISTORY

EDUCATION

ABOUT RANDY F. ESPINAL

I am an applied scientist working at the intersection of biosensors, medical devices, AI/ML, and biomedical signal processing, with a focus on developing data-driven biosensing platforms for translational diagnostics.My current work focuses on nanopore-based single-particle sensing for the analysis of extracellular vesicles, peptides, amino acids, nucleic acids, and cancer-related biomarkers. I combine experimental biosensing systems with signal processing and machine learning to extract quantitative molecular information from noisy, high-frequency electrical signals, including resistive pulse sensing data.I develop end-to-end data analysis workflows for complex biological datasets, including preprocessing, feature extraction, feature engineering, model development, validation, and visualization. My work includes building and comparing supervised and unsupervised machine learning approaches such as logistic regression, Random Forest, support vector machines, discriminant analysis, clustering, and neural-network-based methods when appropriate.In addition to data analysis, I integrate physical and chemical modeling into biosensing workflows, including reaction–transport frameworks such as Damköhler and Péclet analysis to better understand diffusion, enzyme kinetics, and transport behavior in nanofluidic systems.My background also includes analytical chemistry, microfluidic device development, electrode integration, assay development, academic leadership, and student mentorship. This combination allows me to contribute across the full biosensing workflow, from experimental design and device optimization to signal analysis, machine learning, and translational interpretation.Core strengths:• AI/ML for biomedical signal analysis• Nanopore and resistive pulse sensing• Signal processing and feature engineering• Python-based data analysis: scikit-learn, NumPy, SciPy• Model evaluation and validation: cross-validation, ROC/AUC, statistical testing• Microfluidic and electrode system integration• Reaction–transport modeling in nanofluidic systems• Translational biosensing and diagnostics