Ando Shah is a PhD student and researcher at UC Berkeley's School of Information and a Resident Fellow at Microsoft's AI for Good Lab, with a decade of experience applying geospatial machine learning to finance and monitor biodiversity and climate-positive interventions. He builds novel methods to model the Earth's surface from large satellite datasets and translates those models into policy-relevant answers about natural resource extraction and equitable access. Previously he co-founded and led hardware- and software-intensive startups (Ballast Technologies, Tesseract Labs) that shipped products to hundreds of thousands of users, pioneered underwater VR haptics, and developed low-cost wide-area tracking via sensor-fusion algorithms. His earlier career in ASIC and systems engineering at Cisco and Palo Alto Networks included designing high-performance networking silicon, while his research work spans hands-on field projects like underwater camera traps with LIDAR triggers. This blend of production-grade hardware, ML, and policy experience enables him to bridge satellite-scale modeling with deployable verification systems for environmental finance. He also brings international field experience—having learned Swahili during East African pilot deployments—and a portfolio of patents and festival‑recognized VR storytelling that reflect both technical depth and creative breadth.
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