School of Engineering
Showing 401-500 of 521 Results
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Jay Prakash Thakur
Graduate, Stanford Center for Professional Development
BioJay Prakash Thakur is a Senior Machine Learning Engineer at Microsoft specializing in AI agents, multi-agent systems, and responsible agentic AI innovation. Featured in WIRED Magazine for insights on AI agent accountability and the Stanford LEAD Quarterly, Jay bridges technical excellence with strategic thinking to shape the future of human-AI collaboration.
As an open-source contributor to leading agentic frameworks and advisor to industry committees, he focuses on building scalable systems that drive business growth while serving society ethically. His deep expertise spans agentic AI architecture, multi-agent systems, big data, deep learning, and machine learning.
Previously built scalable AI/ML solutions at Amazon and Accenture, Jay has published research on frontier technologies and actively contributes to leading tech communities including IEEE (Senior Member), ACM, and AAAI. He serves as a business and startup advisor, holds multiple patents, and is a global speaker, conference session chair, and panelist on Agentic AI innovation and ethics.
With thought leadership articles reaching global readers and trending on major tech platforms, Jay has established himself as a prominent voice shaping the future of agentic AI development at the intersection of innovation, strategic leadership, and responsible technology. -
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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Juan David Visbal Alcala
Graduate, Stanford Center for Professional Development
BioJuan David is a resilient, hard-working, and enthusiastic leader who is changing the world by solving society's challenges through engineering practices and strategies that optimize, innovate, disrupt, and transform positively.
Juan holds a bachelor's degree in Mechanical Engineering with experience working in cross-functional teams, spanning from engineering, R&D, and other relevant technical functions, to marketing, management, and sourcing to drive profitable results for businesses while exceeding stakeholder expectations.
Analytical thinker and problem-solver driven to further develop industry standards to meet society's next-generation needs in terms of energy demands, agnostic fuel transitions, product reliability, accessibility, and circularity creating long-lasting solutions while safekeeping the environment.
Juan attempts to lead by three main principles that developed as a result of past experiences that turned into learning opportunities:
1. A good leader should not become a figure of authority that disrupts confidence or trust among co-workers. A true leader should bridge communication gaps and become a master at developing meaningful interpersonal relationships in the work environment. Success and productivity are enhanced through effective teamwork that stems from deep bonds of trust driven by communication.
2. A good leader should be a great listener. One should be able to understand and show interest in what each teammate has to share. Sometimes there's no need to look for solutions elsewhere but within the teams. One learns to communicate by listening first.
3. A good leader should be receptive and approachable to anyone willing to come up to them. It's impossible to know whether an initiative, project, or idea has potential if the person to whom it needs to be sold is not prone to receive it. The only crazy idea/question is one that is never asked. -
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.
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Patrick Wang
Graduate, Stanford Center for Professional Development
BioAI, Robotics, Basketball, and everything in between.
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Max Weinacht
Undergraduate, School of Engineering
BioUndergraduate – Class of 2028
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Jerry Yang
Graduate, Stanford Center for Professional Development
BioEngineer; Enterpreneur; Data Scientist; Passion for AI;
Harvard Businness School
CEO of StarRides -
Lei Yin
Graduate, Stanford Center for Professional Development
Biohttps://www.linkedin.com/in/yinlei2000/
