Alessandro Arlotto

Alessandro Arlotto is an Associate Professor at Duke University, affiliated with the Fuqua School of Business, the Department of Mathematics, and the Department of Statistical Science. His research focuses on applied probability, stochastic modeling, stochastic dynamic programming, combinatorial optimization, and their applications to management sciences and economics. Arlotto joined Duke University in 2012 after earning his Ph.D. from the University of Pennsylvania. His work has been published in journals such as the Annals of Applied Probability, Management Science, and Operations Research. He teaches courses including Probability and Statistics, Quantitative Business Analysis, and Stochastic Models at Duke.

Alessandro Arlotto is a researcher at Duke University with a focus on optimal sequential decision-making under uncertainty. His work explores problems in operations research, statistics, and computer science, particularly in online algorithms, dynamic programming, and stochastic optimization. His research includes topics such as regret analysis, optimal hiring and retention policies, and the design of algorithms for sequential selection problems. Arlotto's publications address the performance of online algorithms in dynamic environments, including the multisecretary problem, the stochastic knapsack problem, and the analysis of Markov decision processes. His contributions span both theoretical and applied aspects of sequential decision-making, with applications in service networks, inventory management, and electoral outcomes.