Research, EV Platforms & Ventures

Research Vision

My research sits at the intersection of nanotechnology, extracellular vesicle (EV) biology, and machine learning. I build EV-based tools and signatures to read out brain and immune status from a simple blood draw, with a primary focus on multiple sclerosis (MS) and glial-driven neuroinflammation.

The long-term goal is an EV-based precision neurology platform that can detect smoldering CNS inflammation, predict disability progression, and guide treatment decisions in MS and related disorders—well before irreversible damage appears on MRI.

Patented EV Platforms & Intellectual Property

My work is anchored by two complementary EV technology platforms:

Photocleavable nanoprobe EV isolation platform – I am co-inventor of a photosensitive lipid nanoprobe system that enables rapid, size-selective and high-purity isolation of extracellular vesicles from complex biofluids such as plasma. This platform is protected by a U.S. provisional patent application (63/556,168) and an international PCT application (PCT/US2025/16830) and underpins our work on scalable, high-quality EV preparation for diagnostics and discovery.

EV signature for MS progression – In collaboration with Dr. David Pitt, I co-develop a astrocyte-derived EV small-RNA signature that tracks MS progression and captures chronic glial activation in the CNS. This multiple sclerosis progression EV signature is currently patent pending through Yale Ventures and forms the core intellectual property behind East Rock Diagnostics, where we are translating it into blood-based tests for risk stratification and treatment monitoring in neurodegeneration.

EV Biomarkers in MS & Neurodegeneration

In the Department of Neurology at Yale, my current work focuses on glial-enriched EVs—particularly astrocyte-derived EVs—as a minimally invasive window into CNS innate immune activation. From less than 1 mL of blood, we isolate cell-type-enriched EV populations and profile their small-RNA and protein cargo.

By integrating EV signatures with Expanded Disability Status Scale (EDSS) trajectories, TSPO-PET imaging of glial activation, and longitudinal clinical data, we aim to:

• Differentiate stable from progressive MS phenotypes
• Identify patients at higher risk for future disability progression
• Track response to disease-modifying therapies and emerging interventions
• Extend EV-based signatures to ALS, long COVID, and other neuroinflammatory conditions

These studies provide the discovery and validation backbone for the EV signatures that East Rock Diagnostics and future clinical trials can build on.

Engineering & Biosensing Foundations

My training began at the interface of physics, engineering and biology. During my Ph.D. in the CREAB laboratory (CEA Grenoble), I developed nano-engineered opto-electronic noses, plasmonic biosensors, and peptide-based hybrid nanostructures for volatile organic compound detection, supported by custom machine-learning pipelines for pattern recognition.

As a postdoctoral associate in the laboratories of Dr. Sathish Ramakrishnan and Dr. James E. Rothman at Yale, I helped build bespoke platforms to dissect vesicular biology, including a plasma-membrane-on-a-chip system for single-vesicle measurements and high-throughput luciferase assays to quantify first- and second-phase insulin secretion from β-cells. These engineering tools directly inform how I design EV isolation platforms and analytical workflows today.

Data Science, AI & EV Analytics

Across projects, I build analytic pipelines to handle noisy, high-dimensional EV datasets. This includes feature selection, survival and risk-score modeling, and multi-omics integration of EV miRNA, mRNA and protein data with imaging and clinical outcomes.

The emphasis is on models that are both predictive and interpretable — linking EV signatures back to specific cell types, pathways and mechanisms. This combination of EV biology, engineering, and data science is central to making EV-based diagnostics clinically useful and deployable.

Ventures & Community

East Rock Diagnostics is a Yale-affiliated venture focused on translating the GLAST⁺ EV MS progression signature into clinically actionable blood tests for neurodegeneration. The company builds directly on our patent-pending EV biomarker IP and on the multi-omics datasets generated through my translational research awards.

I also develop digital tools for the EV community, including EVd3x.com (a web-based platform to explore EV cargo across tissues and cell types) and co-organize Yale's Extracellular Vesicle Club, a cross-departmental forum that connects clinicians, engineers and data scientists around EV science and translation.