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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!

News

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.

Lab Members

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.

Research

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.

News

2022 Real Triumphs Graduate

  • [7/2022] Congratulations to solid lab’s Ph.D. Candidate Ahmed Imteaj advised by Prof. M. Hadi Amini for being recognized as the “2022 Real Triumphs Graduate” in the FIU Summer 2022 Commencement Ceremony!  (Link, FIU CEC Coverage)

An Evolutionary Optimization Algorithm for Automated Classical Machine Learning

  • [6/2022] Congratulations to solid lab’s Ph.D. Candidate Leila Zahedi advised by Prof. M. Hadi Amini for successfully defending her Ph.D. Dissertation entitled “An Evolutionary Optimization Algorithm for Automated Classical Machine Learning” on June 29, 2022!

Distributed Machine Learning Algorithms for Resource-Constrained Heterogeneous IoT Environments

  • [5/2022] Congratulations to solid lab’s Ph.D. Candidate Ahmed Imteaj advised by Prof. M. Hadi Amini for successfully defending his Ph.D. Dissertation entitled “Distributed Machine Learning Algorithms for Resource-Constrained Heterogeneous IoT Environments” on May 20, 2022!