ISyE Seminar Series: Alberto Del Pia
"Minimizing Quadratics Over Integers"
Alberto Del Pia
Associate Professor in the Department of Industrial and Systems Engineering, and a member of the Optimization group at the Wisconsin Institute for Discovery
University of Wisconsin-Madison
About the Seminar:
Mixed integer quadratic programming is the problem of minimizing a quadratic polynomial over points in a polyhedral region with some integer components. It is a natural extension of mixed integer linear programming, and it has a wide array of applications. In this talk, I will survey some recent theoretical developments in mixed integer quadratic programming, with a focus on complexity, algorithms, and fundamental properties.
Text Related to the Seminar:
“An approximation algorithm for indefinite mixed integer quadratic programming“
About the Speaker:
Alberto Del Pia is an Associate Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison, and a member of the Optimization group at the Wisconsin Institute for Discovery.
In 2009 he received his Ph.D. from the Department of Mathematics of the University of Padova, under the supervision of Giacomo Zambelli. Then, he worked as a postdoctoral researcher with Robert Weismantel, first in the Institute for Mathematical Optimization of the Otto-von-Guericke University, and then in the Institute for Operations Research of ETH Zürich. In 2013 he joined the Mathematical Programming group of IBM Research as a Goldstine fellow. He then moved to UW-Madison in 2014.
His main research interests lie in theoretical and algorithmic aspects of Mathematical Optimization and Discrete Mathematics, with a focus on Mixed Integer Optimization. The three main problems he considers are (1) Mixed Integer Linear Optimization, (2) Mixed Integer Quadratic Optimization, and (3) Binary Polynomial Optimization. He also works on Discrete Geometry, Polyhedral Combinatorics, and on optimization problems of relevance in Data Science and Machine Learning, like Sparse PCA, Subset Selection, and Clustering problems.
He received the 2023 Egon Balas Prize and the 2017 Young Researchers Prize from the INFORMS Optimization Society, and the 2023 INFORMS Computing Society Prize from the INFORMS Computing Society.