After a two-year postponement due to COVID-19, the bi-annual Stochastic Networks Conference was held the week of June 20-24 at Cornell. The conference, initiated in 1987, is a major forum for researchers to learn of the latest developments and new research directions in stochastic networks.
Stochastic networks is a multifaceted area of research concerned with the modeling, stability, control, performance, approximation, and design of stochastic networks. It gives rise to challenging and subtle mathematical problems, whose solution often requires a combination of ideas and techniques from several branches of mathematics, including probability theory, stochastic processes, analysis, optimization, algorithms, combinatorics, and graph theory. Research in this area is strongly motivated by applications in diverse domains, ranging from the traditional areas of telecommunications and manufacturing to service operations, biological and social networks, revenue management, and health care.
This year's conference, sponsored by ORIE, Cornell's Systems Engineering program, the National Science Foundation, DiDi, INFORMS' Applied Probability Society, the SC Johnson College of Business, and IMS, drew roughly 100 participants and featured a poster session, talks, lightning rounds, meals, a reception, excursions around campus, and more. This year's conference was organized by Professors Jim Dai, David Goldberg, Itai Gurvich, and Jamol Pender and doctoral student Sean Sinclair.