Revenue management (RM) is the application of analytical methodologies and tools that
predict consumer behavior and optimize product availability and prices to maximize a firm's …

Motivated by online decision-making in time-varying combinatorial environments, we study
the problem of transforming offline algorithms to their online counterparts. We focus on …

Many online platforms, ranging from online retail stores to social media platforms, employ
algorithms to optimize their offered assortment of items (eg, products and contents). These …

We consider the design of computationally efficient online learning algorithms in an
adversarial setting in which the learner has access to an offline optimization oracle. We …

The secretary problem is probably the most well-studied optimal stopping problem with
many applications in economics and management. In the secretary problem, a decision …

The increasing availability of real-time data has fueled the prevalence of algorithmic bidding
(or autobidding) in online advertising markets, and has enabled online ad platforms to …

We consider a dynamic pricing problem for repeated contextual second-price auctions with
multiple strategic buyers who aim to maximize their long-term time discounted utility. The …

In a carbon auction, licenses for CO2 emissions are allocated among multiple interested
players. Inspired by this setting, we consider repeated multi-unit auctions with uniform …

Historical data are typically limited. We study the following fundamental data-driven pricing
problem. How can/should a decision maker price its product based on data at a single …

We study the problem when a firm sets prices for products based on the transaction data,
that is, which product past customers chose from an assortment and what were the historical …