This week, we are doing something special. We are pulling together stories, papers, and platforms to celebrate a few of the South Asian Americans who are shaping the future of medicine through artificial intelligence, with rigor, empathy, and a deep sense of responsibility.
We compiled this not just to applaud their brilliance, but to inspire the next wave of doctors, engineers, researchers, and caregivers who wonder where they might fit in. We hope you'll share it , with a student, a colleague, a cousin, or just for yourself. Because this isn’t just their story. It’s yours too.
South Asian Americans who are shaping the future of medicine through artificial intelligence.
From Medicine to Machine Learning and Back Again
Dr. Shinjini Kundu
Physician-scientist. Engineer. Inventor of “transport-based morphometry” - a method that allows MRIs to detect disease years before physical symptoms appear.
🔍 Noteworthy research:
• "Early detection of osteoarthritis using transport-based learning", PNAS (2020)
• "AI in medicine must be explainable", Nature Medicine (2021)
📌 Takeaway: When medicine didn’t have the tools she needed, she built them herself. Cross-disciplinary courage is how revolutions start.
Tools That Listen. Systems That Learn.
Dr. Natalia Khosla
Harvard-trained physician, co-founder of Simbie AI, an AI assistant for medical practices that handles patient follow-ups, EHR integration, and phone-based clinical tasks.
🧠 Impact: Simbie reduces administrative burnout and improves access in under-resourced practices. It’s built for doctors, by doctors.
Dr. Ashutosh Saxena
Stanford professor turned entrepreneur. Founder of Caspar.AI, a platform using ambient sensors and generative AI to monitor elderly well-being, predicting falls, sleep disruption, and cognitive decline. Recognized by MIT Technology Review’s “35 Innovators Under 35”
📌 Takeaway: If medicine is moving into the home, let’s make the home smarter and safer.
What Good Is AI If It Isn’t Fair?
Dr. Nigam Shah
Chief Data Scientist at Stanford Health Care. Co-founder of the Coalition for Health AI (CHAI), which builds transparent, accountable frameworks for clinical AI use.
🔍 Noteworthy research:
• "Learning clinically relevant embeddings of health concepts from EHRs", JAMIA (2019)
• "Bias at warp speed: how AI may exacerbate disparities in emergency medicine", NEJM Catalyst (2020)
📌 Takeaway: The best algorithm in the world is useless if it doesn’t work for everyone. Equity is not optional.
Dr. Pritam Mukherjee, MD, PhD
Dermatologist and ML researcher working on racial bias in diagnostic imaging.
🔍 Related research:
• "Systematic biases in deep learning dermatology algorithms", arXiv (2022)
• Ongoing studies on skin tone diversity in AI dermatology models.
📌 Takeaway: Until every dataset reflects the spectrum of human experience, no diagnosis is truly complete.
Building Systems That See Us
Cardiology & South Asian Risk: South Asians face higher risks of heart disease and traditional models often miss the warning signs. Recent work in Nature Reviews Cardiology and BMJ Open highlights how AI tools that include genetic ancestry, diet, and family history perform better in South Asian populations.
Stanford CARE (Center for Asian Health Research and Education)
Led by South Asian and East Asian researchers, this center is collecting data, running clinical trials, and building culturally relevant models of care for Asian Americans.
📌 Takeaway: Representation isn’t just visibility. It’s being in the dataset and in the room.
Mentorship, Momentum, and Community Power
South Asian Healthcare Leadership Forum (SAHLF)
Founded by Drs. Sachin Jain, Aman Bhandari, Pooja Chandrashekar, Kushal Kadakia, and more. A platform for mentorship, networking, and South Asian-led leadership in digital health, pharma, academia, and care systems.
Wadhwani Institute for AI
Founded by Romesh and Sunil Wadhwani, the institute is solving real-world problems like TB screening, maternal risk scoring, and agricultural health intersections, all with open-source AI tools deployed in partnership with WHO and Indian government bodies.
📌 Takeaway: The future of medicine isn’t being built in isolation, it’s being built in community.
So What Does This All Mean?
It means that the next time your hospital rolls out an AI feature in your EMR or your parents' clinic uses software to flag early signs of chronic illness, you just might be witnessing the work of someone who grew up in a South Asian household where science and service went hand in hand.
This movement isn’t just technical. It’s personal. And it’s ours.
So here's to the changemakers who bring both data and dharma to their work. To those who know that good medicine is about precision, but great medicine is about compassion too. We see you. We’re inspired by you. And we’re better for it.
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