Colloquium

UW-ISyE looks forward to welcoming Dr. Georgia Perakis, Professor at the MIT Sloan School of Management.

UW-ISyE looks forward to welcoming Dr. Santanu Dey, Professor at H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. We develop two general-purpose strong dual formulations for binary MINLPs, motivated by sensitivity analysis and distributed computation. For mixed binary quadratic programs (MBQPs), we show that the copositive dual of Burer’s completely positive...

UW-ISyE looks forward to welcoming Minshuo Chen, assistant professor with the Department of Industrial Engineering & Management Sciences at Northwestern University Diffusion models achieve state-of-the-art performance in various high-dimensional data modeling tasks. These empirical successes challenge conventional wisdom while raising critical concerns. On the one hand, in high-dimensional applications, diffusion models’ strong performance appears to circumvent the...

UW-ISyE looks forward to welcoming Roy Dong Assistant Professor in the Industrial & Enterprise Systems Engineering department at the University of Illinois at Urbana-Champaign. As data-driven methods are deployed in real-world settings, the processes that generate the observed data will often react to the decisions of the learner. For example, a data source may have some...

Assortment and inventory decisions lie at the core of supply chain and retail operations. In practice, these decisions face two fundamental challenges arising from complex customer choice behavior. First, customers often purchase complementary products across categories, which makes category-level decisions interdependent. Second, inventory is limited and customers arrive over time, so product availability changes dynamically...

First-order methods are widely used to tackle data science and machine learning problems with complex structures, such as nonconvexity, nonsmoothness, and stochasticity. However, in many real-world scenarios, the problem structure and parameters can be unknown or ambiguous, creating significant challenges for algorithm design and stepsize selection. In this talk, I will present a novel class...

The rapid progress in GPU computing has revolutionized many fields, yet its potential in mathematical programming, such as linear programming (LP), has only recently begun to be realized. This talk aims to provide an overview of recent advancements in GPU-based first-order methods for LP, with a particular focus on the design and development of cuPDLPx....