Systems Optimization Lab
We are a dedicated group of researchers focused on optimizing engineered systems at scale.
Our goal is to design and develop computational technologies, encompassing mathematical theory, algorithms, and software tools, that can guide decision-makers and stakeholders in understanding the risks and consequences associated with decisions across diverse infrastructure systems.
We strive to make fundamental advances in optimization under uncertainty, machine learning for discrete and scalable optimization, multiscale systems modeling, and high-performance parallel computing. Our primary areas of interest include transportation systems within supply chains and logistics, electrical power systems, and the broader energy infrastructure.
We are driven by a commitment to developing rigorous theoretical foundations that underpin robust algorithms and computational tools.