Current Focus
I recently joined Ultrahuman as Head of Science, where I lead the scientific direction across their physiology platform spanning wearables, metabolic health, and personalized bio-intelligence.
At GrowthStory, I invest in early-stage Deep Tech and Hard Tech like semiconductors, space, defense, robotics, med tech, climate, advanced materials, and AI infrastructure.
At GS Labs, I'm exploring how AI can reshape healthcare delivery and personal wellness, working across voice AI for care, health monitoring, and longevity.
Background
I've spent most of my career building at the intersection of Deep Tech R&D and venture investing.
At Samsung Semiconductor, I wore two hats - developing deep learning-based biosignal algorithms for wearable health monitoring and leading business development to bring Samsung's healthcare chipsets to the Indian market. Before that, at Samsung's Advanced Institute of Technology, I led a small team building smartphone-enabled molecular diagnostics. I hold multiple patents across both roles.
I did my PhD at Caltech in biomedical engineering, researching bio-inspired implants and nanophotonic biosensing. I've also worked at Verily Life Sciences (Google X) and Exponent.
What I Believe
On funding Deep Tech. The venture model needs to evolve to properly support Deep Tech. Fund lifetimes are too short for long-gestation technologies, and risk tolerance is still calibrated to software timelines. I also think the ecosystem would benefit from more fund managers with direct Deep Tech operating experience, not because traditional VCs lack judgment, but because pattern recognition in Deep Tech is fundamentally different. Knowing how long a hardware validation cycle actually takes, what a regulatory pathway costs, or when a technical milestone is genuinely de-risking versus just promising. These instincts are hard to develop without having lived them.
On Indian Deep Tech. India has the ecosystem to build - strong institutions, government support, and a confident founder base. The ecosystem to deliver is catching up. The bigger structural challenge is capital: 98% of growth-stage Deep Tech funding still originates overseas. The fix requires longer fund horizons, LP conviction, and business models that fit the technology, not software playbooks applied to hardware problems.