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Graduate student Mohammed Aburidi defends PhD dissertation

November 18, 2024

Graduate student, Mohammed Aburidi, successfully defended his PhD dissertation, titled "Optimization for Robust and Interpretable Learning on Graphs and Images," on November 18, 2024.  Mohammed is advised by Prof. Roummel Marcia.  His committee members include Prof. Arnold Kim (Applied Mathematics) and Prof. Shawn Newsam (Computer Science and Engineering).

Mohammed received his M.Sc. from Clemson University in 2020.  In Summer 2022, Mohammed served as a research intern at Lawrence Berkeley National Laboratory.  He received the Graduate Division Graduate Student Opportunity Program fellowship for the 2023-24 academic year.  He also received Graduate Student Research funding from the Valley Institute for Sustainability, Technology & Agriculture (VISTA) program for the Fall 2024 semester.  Mohammed will start his postdoctoral engineer position at VISTA in January, 2025. 

Congratulations, Dr. Aburidi!

Dr. Aburidi's selected publications:

  • M. Aburidi and R. Marcia, "Optimal Transport Based Graph Kernels for Drug Property Prediction," in IEEE Open Journal of Engineering in Medicine and Biology, vol. 6, pp. 152-157, 2025, doi: 10.1109/OJEMB.2024.3480708.
  • M. Aburidi and R. Marcia, "Optimal Transport-Based Network Alignment: Graph Classification of Small Molecule Structure-Activity Relationships in Biology," 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Orlando, FL, USA, 2024, pp. 1-5, doi: 10.1109/EMBC53108.2024.10782458.
  • R. Nap, M. Aburidi and R. Marcia, "Contrastive Pre-Training and Multiple Instance Learning for Predicting Tumor Microsatellite Instability," 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2024, pp. 1-7, doi: 10.1109/EMBC53108.2024.10782037.
  • S. Malone, M. Aburidi and R. F. Marcia, "Wasserstein-Based Similarity Constrained Matrix Factorization for Drug-Drug Interaction Prediction," 2024 IEEE Workshop on Signal Processing Systems, Cambridge, MA, USA, 2024, pp. 49-53, doi: 10.1109/SiPS62058.2024.00017.
  • M. Aburidi and R. Marcia, "Topological Adversarial Attacks on Graph Neural Networks Via Projected Meta Learning," 2024 IEEE International Conference on Evolving and Adaptive Intelligent Systems, Madrid, Spain, 2024, pp. 1-8, doi: 10.1109/EAIS58494.2024.10569101.
  • M. Aburidi and R. F. Marcia, "Adversarial Attack and Training for Graph Convolutional Networks Using Focal Loss-Projected Momentum," 2024 IEEE 3rd International Conference on Computing and Machine Intelligence, Mt Pleasant, MI, USA, 2024, pp. 1-5, doi: 10.1109/ICMI60790.2024.10586025.
  • M. Aburidi and R. Marcia, "Wasserstein Distance-Based Graph Kernel for Enhancing Drug Safety and Efficacy Prediction," 2024 IEEE First International Conference on Artificial Intelligence for Medicine, Health and Care, Laguna Hills, CA, USA, 2024, pp. 113-119, doi: 10.1109/AIMHC59811.2024.00029.
  • M. Aburidi and R. Marcia, "Optimal Transport and Contrastive-Based Clustering for Annotation-Free Tissue Analysis in Histopathology Images," 2023 International Conference on Machine Learning and Applications, Jacksonville, FL, USA, 2023, pp. 301-307, doi: 10.1109/ICMLA58977.2023.00049.
  • M. Aburidi and R. Marcia, "CLOT: Contrastive Learning-Driven and Optimal Transport-Based Training for Simultaneous Clustering," 2023 IEEE International Conference on Image Processing, Kuala Lumpur, Malaysia, 2023, pp. 1515-1519, doi: 10.1109/ICIP49359.2023.10222290.
  • M. Aburidi, M. Banuelos, S. Sindi and R. Marcia, "Genetic Variant Detection Over Generations: Sparsity-Constrained Optimization Using Block-Coordinate Descent," 2023 IEEE International Symposium on Medical Measurements and Applications, Jeju, Korea, Republic of, 2023, pp. 1-5, doi: 10.1109/MeMeA57477.2023.10171853.