Rishi Malhan

Enabling AI in legacy industries is like modernizing the cockpit of a time-tested aircraft: the technology may be cutting-edge, but if the controls are not intuitive and reliable, the mission fails. Real impact happens when AI fits operational workflows, earns user trust, meets security and reliability constraints, and can be used confidently by the people closest to the work.

That is where I operate: at the intersection of robotics, AI/ML, and real-world deployment, especially in decision-making and perception systems for industrial environments.

What excites me most is the next phase of Physical AI: moving beyond brittle, hand-crafted heuristics toward systems that learn from operational data, generalize across variation, and continuously improve as new data arrives. In practice, that means building not only models, but the surrounding infrastructure i.e. data collection, curation, training, debugging, validation, and feedback loops that make intelligence usable and trustworthy on real machines.

What I bring:

- Deep technical strength in robotics and AI/ML, grounded in real deployment constraints (latency, robustness, safety, reliability)

- Systems-level thinking across sensing, decision-making, controls interfaces, and production software

- Experience bridging research and production by translating promising ideas into operational capability

- Strong communication across technical and non-technical stakeholders

- A builder’s mindset with startup energy, ownership, and bias toward execution

Long term, I aim to lead as a technology builder and organizational force multiplier: helping teams not only create advanced systems, but build the capability to deliver them repeatedly.