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Riddhi Parasnaik

@riddhiparasnaik

Biomedical AI researcher at Columbia University who developed a CLIP-based model for interpretable, region-specific brain aging analysis.

United States

Message

What I'm looking for

I'm targeting ML/AI roles where rigorous research translates directly into clinical impact.

At Columbia University, I developed a CLIP-based multimodal model to predict BrainAGE from T1-weighted MRI, designed for interpretable, region-specific aging analysis. My research also includes multimodal lung cancer prognosis and graph neural networks for modeling cell fate transitions.

At Madabhushi Lab, Emory University, I engineered a deep learning pipeline for thoracic CT analysis that achieved a 0.88 Dice score. At Koita Centre for Digital Health, IIT Bombay, I developed and benchmarked melanoma classification pipelines, achieving 93% AUC, and deployed a Flask-based triage app.

Experience

Work history, roles, and key accomplishments

Research Fellow

Columbia University

Aug 2025 - May 2026 (9 months)

Developed a CLIP-based multimodal model to predict BrainAGE from T1-weighted MRI, designed for interpretable, region-specific aging analysis.

CLIP Multimodal Learning MRI PyTorch Deep Learning

Participant

MIT GrandHack 2026

Mar 2026 - Mar 2026 (0 months)

Selected among 5000 applicants; built Lisa, a fully automated pre-consultation robot with LLM-powered history-taking and FHIR-compliant EHR transcription, reducing documentation burden.

LLM FHIR Electronic Health Records (EHR)Python Flask

Undergraduate Research Assistant

Madabhushi Lab, Emory University

Apr 2024 - Apr 2025 (1 year)

Engineered a multi-task deep learning pipeline (U-Net + radiomics) across 150+ thoracic CT scans to quantify vessel tortuosity, organ volumes, and lymph node segmentation, achieving 0.88 Dice score.

U Net Radiomics Computed Tomography (CT)PyTorch Deep Learning

Project Fellow

Koita Centre for Digital Health, IIT Bombay

Jun 2024 - Mar 2025 (9 months)

Developed and benchmarked 8 ML classification pipelines on ISIC and HAM10000 datasets, achieving 93% AUC on melanoma detection, and deployed a Flask-based triage web app.

ResNet50 Haralick Gan Flask Machine Learning

Education

Degrees, certifications, and relevant coursework

Columbia University

Master of Science, Biomedical Engineering

2025 -

Grade: 3.9/4.0

Pursuing a Master of Science in Biomedical Engineering with a GPA of 3.9/4.0.

Columbia University

Bachelor of Engineering, Biomedical Engineering

Grade: 9.85/10

Completed a Bachelor of Engineering in Biomedical Engineering with Honors in AI & ML, achieving a GPA of 9.85/10 and graduating as Class Valedictorian.