School of Engineering
Showing 101-150 of 197 Results
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Ruizhe Jia
Assistant Professor of Management Science and Engineering
BioI am an Assistant Professor in the Department of Management Science & Engineering at Stanford University. I earned my Ph.D. in Operations Research at Columbia University, advised by Prof. Agostino Capponi, and completed my B.S. and M.A. in Mathematics at UCLA.
My research sits at the intersection of financial technology, market microstructure, and mechanism design. I study how financial markets function and how they can be redesigned for greater efficiency and fairness, with a particular focus on decentralized finance (DeFi) and blockchain-based trading. My work spans three areas:
Market microstructure — analyzing trading behavior and designing better financial markets.
FinTech and DeFi — examining how cryptographic tools and decentralized protocols reshape financial transactions.
Incentives in financial technology — addressing misalignments that emerge in crypto-finance and proposing mechanisms that improve adoption and efficiency.
I believe finance is a social science that benefits from active engagement with real markets. I work closely with both industry and regulators to ensure my research not only advances theory but also informs practice and policy in digital assets and financial technology. -
Enyi Jiang
Graduate Visiting Researcher Student, Computer Science
BioI am a third-year Computer Science Ph.D. student at the University of Illinois at Urbana-Champaign, advised by Prof. Sanmi Koyejo and Prof. Nancy Amato. I am broadly interested in trustworthy machine learning, especially in AI safety and alignment.
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Jikai Jin
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2023
BioI am currently a Ph.D. student of the The Institute for Computational and Mathematical Engineering (ICME) at Stanford university. Prior to joining Stanford, I obtained my bachelor degree in computational mathematics at the School of Mathematical Sciences, Peking University, fortunately having Prof. Liwei Wang as my research advisor. My research is highly interdisciplinary across machine learning, statistics, operations research. While primarily focusing on theoretical aspects, the ultimate goal of my research is to develop state-of-the-art solutions for important real-world problems.
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Ramesh Johari
Professor of Management Science and Engineering and, by courtesy, of Electrical Engineering
BioJohari is broadly interested in the design, economic analysis, and operation of online platforms, as well as statistical and machine learning techniques used by these platforms (such as search, recommendation, matching, and pricing algorithms).
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Dave Johnson
Affiliate, Programs
Bioplease see: https://law.stanford.edu/directory/david-johnson/
