Our Vision
A future where AI advances clinical care safely as AI systems become more capable and autonomous while keeping clinicians at the centre of every management decision for our patients.
Centre for Responsible Autonomous Systems in Healthcare
An Interdisciplinary Research Studio Where Clinical Expertise Drives AI Development
Our Mission
To build the datasets, evaluation frameworks, and foundations that healthcare AI needs to be developed and deployed safely across the patients, workflows, and contexts where it will actually be used.
What The Lab Has Built Since Founding
10+
Most RSNA 2025 abstracts by any Indian healthcare AI lab
15+
Papers & abstracts at RSNA, MICCAI, NEJM AI, IJRI, KCR, AOCR since 2025
10+
Collaborating institutions across India, US, Europe, and Asia
90+
Clinicians, researchers, and engineers across CRASH Lab projects
How we started
Since starting the research group in April 2025, CRASH Lab has grown from a single research cohort into a nationwide effort spanning AI evaluation, data infrastructure, and clinician-AI collaboration. Our work is extremely fast-paced and is built around the thesis that healthcare AI should be evaluated by experts under real world scenarios. The timeline below traces what we've shipped since.
CRASH Lab Journey: The Milestone Timeline
April 2025
CRASH Lab Founded
CRASH Lab began as a small cohort of physicians, primarily radiologists, and engineers working together on radiology AI research projects for RSNA.
May-June 2025
Scaling the Research Studio
As our initial projects expanded, more physicians across specialties, medical students, researchers, psychologists, and engineers joined us. This helped CRASH Lab evolve from a radiology AI initiative into a broader healthcare AI research lab.
July 2025
Academic Validation
CRASH Lab's early work received academic validation through accepted research across healthcare AI and medical imaging venues.
Sept 2025
RadLE Benchmark Unveiled
We launched Radiology's Last Exam, a benchmark designed to test how frontier AI models perform against expert radiology reasoning.
Nov 2025
RSNA Research Milestone
We reached a major RSNA milestone with 11 accepted abstracts, reflecting our growing research output in radiology AI.
2026 and Beyond
National Research Collaborations
We began securing support from leading national bodies, including ANRF, DST, and the IndiaAI Mission, to advance responsible healthcare AI research.
HOW WE DIVIDE OUR WORK
Four Pillars. One Mission.
Each pillar reinforces the others to form the foundation for safe and responsible healthcare AI.
01
Opens the full pillar brief in a dialog. Press Enter.Data Commons
National and International scale clinical data networks
- Consortia across public and private institutions
- DPDP Act compliant data sharing
- Networks of public and private clinics powering national-scale AI
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02
Opens the full pillar brief in a dialog. Press Enter.Standards & Benchmarks
Real-world, complex clinical benchmarks for frontier medical AI systems
- Hard benchmarks grounded in real clinical cases
- Bias and subgroup audits
- Failure-mode taxonomies for safer deployment
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03
Opens the full pillar brief in a dialog. Press Enter.Foundational AI Models for India
Foundation models for South Asian population
- Models that work for South Asian patients
- Novel geometric and topological architectures
- Bias mitigation in AI models
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04
Opens the full pillar brief in a dialog. Press Enter.Human-Centric Multi-Agent Systems
Clinician-centred AI, with framing of policies built for what comes next
- Multi-agent systems co-designed with clinicians
- Forward-looking policies for autonomous AI
- Trusted, edge-deployable AI agents
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Each pillar feeds the next: data → benchmarks → models → deployment.
Let’s Accelerate Healthcare AI Innovation Together
Whether you're a clinician, researcher, or industry partner — we'd love to collaborate.