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Student Spotlight: Yinjun (YJ) Wang

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Meet Yinjun (YJ) Wang, an incoming PhD student in MS&E.

HOMETOWN
Qingdao, China

WHERE I LIVED BEFORE STANFORD
Qingdao, China

ALMA MATER
The Chinese University of Hong Kong, Shenzhen

MAJOR
Mathematics

RESEARCH THEMES MY WORK REPRESENTS
AI & Data Science

Academic and work experience

Before joining MS&E, I was an undergraduate student at The Chinese University of Hong Kong, Shenzhen. I studied math in college, and soon became interested in optimization. Optimization is a powerful tool for modeling the world and informing decisions, but the mathematical prerequisites often prevent many practitioners from using it. One challenge is properly tuning certain parameters to make the pipeline work effectively. Motivated by the goal of making optimization pipeline more accessible, I designed and open-sourced tuning-free algorithms for various optimization problems.

Advancements in AI and data infrastructures are driving business stakeholders to rethink how these innovations can be effectively integrated into decision-making processes. Pursuing a PhD in MS&E will enable me to achieve my goal of making such modern decision-making pipelines more accessible to practitioners.

Impact I hope to have in my field and the world

I aim to connect tools across machine learning, optimization, causal inference to build AI-powered analytics systems that make decision-making processes more evidence-based and streamlined.

Interests and hobbies

I enjoy reading, as well as playing table tennis and squash. Most of the time, I just hang out with friends, doing random things.

Published September 23, 2024.

Meet the 2024 cohort of incoming PhD students