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
18 publications
Continuous Optimization
conditional gradient algorithms; non-smooth optimization; block-iterative and distributed optimization algorithms; accelerated methods; online learning algorithms
10 members
5 projects
90 publications
Integer Optimization
mixed-integer (nonlinear) programming; nonconvex optimization; exact linear programming; cutting planes; branch-and-bound; SCIP Optimization Suite
14 members
6 projects
63 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
9 members
4 projects
17 publications
Robust and Explainable Learning
robustness and interpretability of artificial intelligence; compression of deep neural networks; optimization methods for deep learning; learning for combinatorial optimization
17 members
6 projects
38 publications