Sustainability, Optimization, and Learning for InterDependent networks laboratory (solid lab) is an interdisciplinary research group bridging the gap between theory and real-world. Interdependent networks require highly efficient computational algorithms to deal with large-scale optimization, learning, and ultimately decision making problems. Our goal is to leverage our solid mathematical background to develop novel algorithms tailored for various engineering applications. At solid lab we aim at solidifying critical infrastructures leveraging computing and information sciences, i.e., we are connecting Computer Science and Engineering worlds!
We are hiring. Please see the research tab for ongoing projects. Multiple PhD/MSc positions with financial support are available. Undergraduate students who are interested in research are welcome to visit our lab and hear about ongoing projects.
We are a diverse group of researchers who are passionate about interdisciplinary research. Our core strength is in respecting diversity, being inclusive, and providing a nurturing environment to explore novel interdisciplinary ideas together.
Our lab focuses on interdisciplinary topics at the intersection of optimization and learning theory, interdependent networks, and sustainability. For more details about ongoing projects and recent publications, please see the research page.