Xi Chen

Biography

Xi Chen is a Full Professor and Andre Meyer Faculty Fellow in the Department of Technology, Operations, and Statistics at the New York University Stern School of Business. He is also an affiliated faculty member of the Courant Institute of Mathematical Sciences and the Center for Data Science at NYU.

Professor Chen’s research lies at the intersection of machine learning, artificial intelligence, statistics, and operations research, with applications to digital platforms, online advertising, dynamic and personalized pricing, recommender systems, algorithmic fairness and privacy, and quantitative finance. In recent years, his work has expanded into the economics of blockchain, Web3, decentralized finance, and real-world asset (RWA) tokenization, integrating mechanism design, tokenomics, and AI-driven decision systems.

His research has been published extensively in leading academic journals, including Management Science, Operations Research, Journal of the American Statistical Association, Annals of Statistics, Journal of Machine Learning Research, and Mathematics of Operations Research. He is the co-author of Web3: Blockchain, the New Economy, and the Self-Sovereign Internet (Cambridge University Press) and co-editor of Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow (Springer), as well as The Elements of Joint Learning and Optimization in Operations Management (Springer).

Professor Chen has received numerous honors for his scholarly contributions. He is an elected Fellow of both the American Statistical Association (ASA) and the Institute of Mathematical Statistics (IMS), a recipient of the NSF CAREER Award and the COPSS Emerging Leader Award, and an elected member of the International Statistical Institute. He was named to the Forbes 30 Under 30 (Science) list and selected by Poets & Quants as one of the World’s Best 40 Under 40 MBA Professors.

From 2021–2023, Professor Chen served as a Principal Research Scientist at Amazon Ads, where he led modeling and optimization efforts for large-scale advertising marketplaces, including auction design, supply forecasting, delivery optimization, pacing, bidding strategies, and LLM-enhanced pipelines. His work directly influenced the core advertising infrastructure deployed at a global scale. He has also collaborated extensively with industry partners, including Google, Meta, Adobe, Bloomberg, and J.P. Morgan, on research and applied projects in digital markets, algorithmic decision-making, privacy, and financial forecasting, receiving multiple distinguished faculty research awards from these organizations.

Professor Chen currently serves as an Expert Affiliate at Compass Lexecon, where he provides economic and technical expertise on artificial intelligence, digital platforms, and Web3 in litigation, regulatory, and advisory contexts. He plays an active role in academic service as Area Editor for Operations Research and Associate Editor for the Journal of the American Statistical Association, Annals of Statistics, and Management Science.

Professor Chen received his Ph.D. in Machine Learning from Carnegie Mellon University’s School of Computer Science and completed postdoctoral training under the supervision of Professor Michael I. Jordan at the University of California, Berkeley.

Research Interests

• Machine Learning and Generative & Agentic AI
• High-dimensional Statistics, Statistical Inference, and Data-Driven Decision Making
• Dynamic Pricing and Revenue Management
• Digital Platforms, Online Advertising, and Algorithmic Fairness & Privacy
• Blockchain, Web3, Tokenomics, and Decentralized Finance
• Quantitative Finance and AI-Driven Financial Systems

Academic Background

Ph.D., Machine Learning
Carnegie Mellon University, School of Computer Science

M.S., Industrial Administration and Operations Research
Carnegie Mellon University, Tepper School of Business

Awards & Appointments