Alexandre Belloni has been intrigued by operations research and optimization problems since his days at as an electrical engineering undergrad at the Pontifical Catholic University of Rio de Janeiro, back in his home country of Brazil. Further schooling just cemented that. His master’s in mathematical economics at the Institute for Pure and Applied Mathematics, also in Rio de Janeiro, “happened to have a strong optimization track,” he said. “Once I got there, the economics influence started to kick in,” he says. “And, given my background, I was always looking for the intersection of operations research and economics.”
For his PhD, Belloni worked on optimization and econometrics at the MIT Operations Research Center. His interest in economics continued to influence his academic path and most of his current research is focused on mechanism design problems, which he describes as “a broad class of ways to allocate resources.” “For example, auctions are a classic way that you can allocate an item and it is especially useful in cases where it’s difficult to price the value of the item.”
Belloni says mechanism design is an incredible field to work on. “Not only there are many interesting perspectives to consider — such as information, computational, approximations, robustness, dynamics — but we also see several industry problems requiring to coordinate decentralized systems.”
Since 2007, Belloni has also taught at the Fuqua Business School at Duke University, where he is currently the John D. Forsyth Professor of Decision Sciences. In 2018, he was recruited to become an Amazon Scholar, joining the company in that capacity in January 2019. “I always thought that the best research is the one that is motivated by empirical, real problems. Amazon gives you a great opportunity to see the real problems,” he says.
Since then, he has been studying problems related to mechanism design and machine learning at Fulfillment by Amazon (FBA), the subdivision of Amazon’s Supply Chain Optimization Technologies (SCOT) organization for third-party sellers who use Amazon’s storage and fulfillment capabilities.
One of the challenges Belloni and his FBA colleagues are currently addressing has to do with capacity management. Third-party sellers own and control their own inventories, and Amazon, with limited information, determines how to both balance the demand for space and ensure fulfillment center capacity is used efficiently and is available for products that customers love. “There has been tons of amazing work and we continue to obsess on finding better ways to manage capacity,” Belloni said.
Coordinating and optimizing allocations is also at the core of a recent work by Belloni and colleagues. In the paper “Optimal Auction Design with Deferred Inspection and Reward”, the authors develop a mechanism to incentivize buyers within an auction to bid higher by rewarding with a bonus the ones whose bids are closer to the true value of the item. This strategy can only be used in certain settings, where it is possible to monitor how the buyer is monetizing that good.
In this interview, Belloni discusses how he and his co-authors — Saeed Alaei, Ali Makhdoumi and Azarakhsh Malekian — came up with this new auction design that is especially suitable for digital goods and how it may impact revenues.