School of Engineering
Showing 1-50 of 252 Results
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Elijah Appelson
Masters Student in Management Science and Engineering, admitted Autumn 2025
BioElijah Appelson is an activist, mathematician, and computational social scientist. From 2023 to 2025, he served as the first data analyst/scientist at the ACLU of Louisiana, focusing on immigration, policing, and the broader criminal legal system. There, he conducted statistical analyses for legal cases, supported policy change, and developed educational tools, including "Visualizing Police Violence in Louisiana" and "Policing in Louisiana: By the Facts". He is skilled in web scraping, predictive modeling, and data storytelling, and uses these tools to create accountability. Prior to the ACLU, he held roles at the Center for Community Alternatives and the Vera Institute of Justice, intersecting technical expertise with a commitment to civil rights. His academic interests center on using machine learning to hold state violence accountable through education, policy, and law.
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Noah Benjamin-Pollak
Ph.D. Student in Management Science and Engineering, admitted Autumn 2022
BioNoah Benjamin-Pollak (noahabp@stanford.edu) is a PhD candidate in Management Science & Engineering at Stanford University. He is a member of the Center for Work, Technology, and Organization (WTO). His research focuses on how different professions interact, particularly how authority and expertise are utilized in cross-occupational contexts. His current research uses ethnographic methods to understand cross-occupational collaboration between engineers and traditional business employees. Additionally, he is focused on understanding how expertise and expert authority are built and communicated between experts and non-expert audiences.
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Jesse DeRose
Masters Student in Management Science and Engineering, admitted Autumn 2024
BioHow can work balance profit and social impact? What if employees were intrinsically motivated to show up every day?
I help leaders answer these questions because we all deserve purposeful work. Whether that’s cultivating emotional intelligence, fostering psychological safety, or removing process friction, healthy work is proven to increase productivity, creativity, and decision-making.
Combining industry research with a decade of experience building digital transformation programs, I help my clients build human-centered solutions that align their people, processes, and technology to make data-driven business decisions. -
Junting Duan
Ph.D. Student in Management Science and Engineering, admitted Autumn 2020
BioJunting Duan is a PhD candidate in the Department of Management Science and Engineering (MS&E) at Stanford University. Prior to joining Stanford, she received her B.S. in Mathematics and Applied Mathematics from Peking University in 2020.
Junting's research interests lie broadly in data-driven decision-making, focusing on statistical inference and machine learning, with applications to causal inference and finance. Her research develops new methodologies with rigorous statistical foundations that enable reliable decision-making with complex and imperfect data, and lies at the intersection of (1) statistical learning for high-dimensional data; (2) causal inference; and (3) machine learning for finance and risk management. Her work has been recognized through publications and revisions at top journals including Management Science and the Journal of Econometrics, as well as invitations to present at major conferences such as the American Economic Association Annual Meeting, the NBER-NSF Time-Series Conference, the NBER Forecasting & Empirical Methods Conference, and the INFORMS Annual Meeting.
Visit her personal website for more details: https://juntingduan.com.
