School of Engineering
Showing 1,601-1,700 of 2,284 Results
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Jon Saad-Falcon
Ph.D. Student in Computer Science, admitted Summer 2023
BioCheck out my personal website for more information: https://jonsaadfalcon.com/
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Adam Sabet
Masters Student in Electrical Engineering, admitted Autumn 2026
Current Research and Scholarly InterestsMy interests center on robotics and control, particularly manipulation, embedded autonomy, and learning-based approaches to decision-making in uncertain environments. I'm building toward research in these areas as I begin my M.S. at Stanford.
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Aadesh Salecha
Masters Student in Computer Science, admitted Autumn 2024
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 -
Anna Sebastio
Masters Student in Aeronautics and Astronautics, admitted Autumn 2026
Intramural Official, Recreation Competitive SportsBioRecent Aerospace Engineering graduate from Illinois Institute of Technology and incoming M.S. student at Stanford University, seeking to apply and expand my expertise in aerodynamics, propulsion, and aerospace systems. Interested in modelling and performance optimization of high-performance aircraft and propulsion systems, with the goal of developing innovative and sustainable flight technologies.
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Yash Shah
Ph.D. Student in Computer Science, admitted Autumn 2025
Current Research and Scholarly InterestsMy research interests lie in developing neuroconnectionist mechanistic models of the brain that deepen our understanding of neural computation and representations. I aim to explore how physiological and anatomical constraints shape cortical topography and, in turn, scaffold development. I am particularly intrigued by observing certain behaviors emerge from mechanistic models, even when the model was not optimized to do so.
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Baiyu Shi
Ph.D. Student in Mechanical Engineering, admitted Autumn 2023
Current Research and Scholarly InterestsMy research combines electronic skin, tactile sensing, and robot learning to enable dexterous manipulation and safe physical interaction. I develop scalable, stretchable sensing systems that help robots perceive and respond to contact. My broader interests include novel sensing modalities, human-robot interaction, mechanical design, and wearable technologies.
