Research Areas
The research of IOL spans 5 areas, encompassing optimization theory, algorithm design, machine learning, operations research, combinatorics, quantum computing, and applications in energy, transportation, and healthcare. Select an area below to learn more:
Computational Mathematics
computer-assistance in proofs; flag algebras in combinatorics; algebraic methods in computation; interactive theorem provers; learning-based heuristics
8 members
3 projects
20 publications
Continuous Optimization
conditional gradient algorithms; non-smooth optimization; block-iterative and distributed optimization algorithms; accelerated methods; online learning algorithms
11 members
5 projects
94 publications
Efficient and Sustainable AI
deep learning efficiency; sustainable AI; deep learning optimization; AI4Science
17 members
6 projects
47 publications
Integer Optimization
mixed-integer (nonlinear) programming; nonconvex optimization; exact linear programming; cutting planes; branch-and-bound; SCIP Optimization Suite
16 members
6 projects
74 publications
Quantum Mathematics
tensor decompositions and tensor-based algorithms; operator theory (transfer operators); numerical methods PDE; data-driven and kernel-based techniques; Bell nonlocality; entanglement quantification
7 members
4 projects
17 publications