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BioAadesh Salecha is a Founding Engineer at Hyfin (hyfin.capital), where he is building GAIA, a platform that synthesizes asset performance and market data to power clean energy loan origination. He designs agentic data pipelines that combine LLMs and web scraping to create data for a new asset class with no track record, and risk intelligence tools aimed at closing the $4T+ clean energy financing gap across South Asia and Africa.

Aadesh completed his MS in Computer Science at Stanford in 2026. At Stanford, he worked as an AI/ML researcher with Prof. David Lobell and the Center on Food Security and the Environment at the Stanford Doerr School of Sustainability, building geospatial machine learning pipelines on Google Earth Engine, Landsat, and Sentinel-2 imagery to detect tree species across cropland in the Global South. This work supports verification of the 5+ Gt CO2/year sequestration potential of integrating trees into global cropland. He also won Stanford's first Green AI Hackathon with a geothermal site prediction system built on AlphaEarth satellite embeddings (findgeothermal.com).

Earlier at Stanford, he worked with Prof. Johannes Eichstaedt on applying cognitive science and psychometrics to evaluate large language models. Their paper showing that LLMs exhibit human-like social desirability biases was published in PNAS Nexus and covered by WIRED.

Previously, Aadesh was an AI/ML Engineer at Amazon (AWS SageMaker HyperPod), where he built an agentic AI system to auto-resolve ML infrastructure failures and reduced GPU energy waste by about 200 kg CO2e per day. Before Stanford, he was a Senior Software Engineer on the Financial Platform team at DraftKings. He received his BS in Computer Science, summa cum laude, from the University of Minnesota, where he researched misinformation spread with Prof. Jaideep Srivastava.

Website: https://aadeshsalecha.github.io
LinkedIn: https://www.linkedin.com/in/aadesh-salecha
Google Scholar: https://scholar.google.com/citations?user=Cnwzl3oAAAAJ