School of Engineering
Showing 1-100 of 251 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
Hourly Student Employee- Practitioner Course Program, Ethics In SocietyBioHow 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. -
Martin Jose Gonzalez
Ph.D. Student in Management Science and Engineering, admitted Autumn 2025
BioA PhD student in Management Science & Engineering, Martin researches the impact of AI on organizations through the Center for Work, Technology and Organization.
With master's degrees from Columbia and the London School of Economics, Martin frequently lectures at top-tier institutions including Stanford, Wharton, and INSEAD. His professional background includes roles at BCG and Google, where he focused on organizational design, cultural transformation, and leadership development. -
Yinbin Han
Ph.D. Student in Management Science and Engineering, admitted Autumn 2025
BioYinbin Han is a Ph.D. student in the Department of Management Science and Engineering at the Stanford University. Before joining Stanford, Yinbin was a Ph.D. student in the Department of Finance and Risk Engineering at the New York University from 2024 - 2025 and in the Epstein Department of Industrial and Systems Engineering at the University of Southern California from 2021 - 2024. Yinbin is fortunate to be co-advised by Prof. Renyuan Xu (Stanford) and Prof. Meisam Razaviyayn (USC). Yinbin obtained his B.S. in Mathematics from the Chinese University of Hong Kong, Shenzhen, where he was advised by Prof. Zizhuo Wang. Yinbin's research interests include diffusion models, reinforcement learning, stochastic control and nonconvex optimization.
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Kent Hippler
Ph.D. Student in Management Science and Engineering, admitted Summer 2025
BioKent Hippler is a PhD student in the Decision and Risk Analysis (DARA) Group in Stanford's Department of Management Science and Engineering, advised by Dr. Elisabeth Paté-Cornell. His current research focuses on risk attitudes in AI Decision Support Systems.
Prior to pursuing his PhD, Kent served as a Nuclear Surface Warfare Officer in the U.S. Navy, supporting three western Pacific deployments aboard the USS Anchorage and USS Theodore Roosevelt. He later worked as a Systems Engineer at Maxar Technologies and a Software Engineer at Amazon. Kent holds a B.S. in Nuclear Engineering, summa cum laude, from the University of Florida (2016) and an M.S. in Management Science and Engineering from Stanford (2025), where he worked with the Language Data and Reasoning Lab under the advisement of Dr. Amin Saberi. -
Andrew Hong
Masters Student in Management Science and Engineering, admitted Autumn 2022
BioI study the intersection of machine learning and social sciences to better align tech with society and use computational methods to understand human behavior. My research focuses on building software and statistical methods to quantify fairness of various electoral voting systems. Now, I'm a Machine Learning Analyst in Google's Trust & Safety Team while finishing my Masters in Management Science & Engineering.
MS: Management Science & Engineering, concentration in computational social sciences
BA: Data Science & Social Systems, concentration in socio-political behavior analysis
