Dean's Office
Showing 401-500 of 559 Results
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Oscar Rodriguez
Graduate, Stanford Center for Professional Development
BioPursuing a Graduate Certificate in Artificial Intelligence. Outside of Stanford, I work on Machine Learning infrastructure for Gemini training setups at Google.
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Jack Topper
Graduate, Stanford Center for Professional Development
BioJack Topper is a Scientific Software Engineer at NASA’s Community Coordinated Modeling Center (CCMC), where he designs and operates large-scale scientific data and modeling systems supporting the global space-weather research community. His work focuses on automating high-performance computing workflows, building resilient data pipelines, and translating complex scientific models into reliable, user-facing services.
He collaborates closely with domain scientists to bridge research objectives and production-grade software, and has taken on technical leadership responsibilities spanning system architecture, reliability, and user adoption. His interests sit at the intersection of optimization, decision systems, machine learning, and large-scale infrastructure, with an emphasis on how mathematical models and data-driven methods inform real-world operational decisions.
Jack is currently pursuing Stanford’s Data, Models, and Optimization Certificate through the Stanford Center for Professional Development, including coursework in convex optimization and related decision-science foundations. -
Nguyen Dang Khoa Tran
Graduate, Stanford Center for Professional Development
BioA professional practitioner in quantitative finance specializing in portfolio optimization, with a keen interest in machine learning and artificial intelligence
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Mauricio Valencia
Director Corporate Relations, School of Engineering - External Relations
Current Role at StanfordDirector of Corporate Relations, School of Engineering
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Aswine Visva
Graduate, Stanford Center for Professional Development
BioAswine Visva is a senior software engineer at NVIDIA working on machine learning systems for autonomous vehicle perception. His work focuses on building and deploying 3D deep learning perception models and optimizing them for real-world deployment. Prior to joining NVIDIA full time, he completed multiple internships working on perception and machine learning infrastructure while studying at the University of Waterloo.
