Mahdis Bayani

Mahdis is a PhD candidate of Polytechnique Montreal under supervision of Louis-Martin Rousseau and Yossiri Adulyasak. She is graduated from Polytechnique Tehran, Iran in both B.Sc. and M.Sc. Mahdis is interested in combining Operations Research and Machine Learning algorithms to find patterns in quadratic combinatorial optimization problems. Currently, her research revolves around solving some Binary Quadratic Problems using decomposition methods.

Journal and Conference Publications - 2024

Bayani M, Adulyasak Y, Rostami B, Rousseau L-M, (2024), A Dual Bounding Framework Through Cost Splitting for Binary Optimization, INFORMS Journal on Computing. https://doi.org/10.1287/ijoc.2021.0186