Clinical Data · 2026
Publication record pending verification: Clinical Data
To be confirmed · To be confirmed
Vision Exploration & Data Analytics Lab
Advancing biomedical AI through disciplined research, mentorship, and evidence.
विद्यामृतमश्नुते
VEDAs brings together computational AI, health data analytics, and Indian knowledge tradition to support rigorous research training, transparent project evidence, and accountable academic workflows.
Research pillars
Focused areas for biomedical AI work
01
Biomedical Vision
Research area for imaging, annotation workflows, and model evaluation in biomedical AI.
computer visionmodel evaluationannotation
02 Research Evidence Systems
Research area for GitHub-based contribution evidence, weekly review, and reproducible project records.
GitHub evidencereproducibilitymentorship
03 Clinical Data Analytics
Research area for structured health data, cohort analysis, and evidence-aware dashboards.
analyticscohort designvalidation
Featured projects
Research with traceable evidence
Projects are designed around explicit scope, mentor review, GitHub evidence, and reviewable outputs rather than vague participation.
Publications
Selected outputs
Research Systems · 2026
Publication record pending verification: Research Systems
To be confirmed · To be confirmed
Biomedical Vision · 2025
Publication record pending verification: Biomedical Vision
To be confirmed · To be confirmed
News and events
Lab activity
news · 8/7/2026
VEDAs platform configuration prepared
Initial website and portal structure prepared for verified lab content and operational configuration.
news · 1/7/2026
Internship OS workflow drafted
Lifecycle, approvals, evidence tracking, documents, notifications, and service records are represented in the portal.
events · 15/7/2026
Biomedical AI reading group schedule pending
Event record reserved for a lab reading group or project review after schedule confirmation.
VEDAs Internship OS
A research training system built for accountability.
The portal connects application review, project assignment, weekly updates, GitHub evidence, milestone approvals, certificates, LORs, deboarding, and archive workflows.