Research in this area focuses on developing efficient and scalable algorithms for solving large scale optimization problems in engineering, data science and machine learning. Our work also studies optimal decision making in networked settings, including communication networks, energy systems and social networks. The multi-agent nature of many of these systems also has led to several research activities that rely on game-theoretic approaches.
Latest news in optimization and game theory
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
The Department of Electrical Engineering and Computer Science (EECS) is proud to announce multiple promotions.
The series aims to help policymakers create better oversight of AI in society.
Founded in 2019, The EECS Alliance program connects industry leading companies with EECS students for internships, post graduate employment, networking, and collaborations. In 2023, it has grown to include over 30 organizations that have either joined the Alliance or participate in its flagship program, 6A.
Justin Solomon applies modern geometric techniques to solve problems in computer vision, machine learning, statistics, and beyond.