Amjad Seyedi
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Doctoral researcher |
๐ค About me
I am a Doctoral Researcher at the University of Mons, supervised by Prof. Nicolas Gillis. My current research sits at the intersection of Matrix Theory and Optimization, specifically developing matrix factorization and low-rank approximation methods for Trustworthy Machine Learning. I aim to leverage these mathematical tools to enhance robustness, interpretability, and fairness in high-dimensional data and network analysis. Previously, I was a Graduate Research Assistant at the University of Kurdistan, where I led the Algebraic Machine Learning (AML) team and focused on representation learning. I hold an MSc in Artificial Intelligence from the same institution, where my work with Dr. Parham Moradi and Dr. Fardin Akhlaghian focused on matrix factorization for semi-supervised learning and recommender systems. I also hold a Bachelorโs degree in Software Engineering.
๐ Research interests
๐ง Machine Learning: representation learning, deep learning, unsupervised learning
๐ก๏ธ Trustworthy ML: robustness, generalization, interpretability, fairness
๐งฎ Applied Mathematics: linear algebra, optimization, low-rank approximation
๐ Applications: healthcare, recommender systems, remote sensing
๐ข News
Upcoming
๐๏ธ I will attend the 2026 International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 4-8, 2026.
๐๏ธ I will attend the “SOCN: Identification in Dynamic Networks course (Prof. Paul M.J. Van den Hof)”, at the Vrije Universiteit Brussel, Belgium, March 4-6, 2026.
Recent news
๐ฐ Our paper, Encoder-Decoder Symmetric Nonnegative Matrix Tri-Factorization for Graph Clustering, has been accepted for the 2026 International Conference on Acoustics, Speech, and Signal Processing.
๐ฐ Our paper, Semantic Encoder-Decoder NMF with Kullback-Leibler Divergence, has been accepted for publication in International Journal of Machine Learning and Cybernetics 2026.
๐ฐ Our paper, Community Detection via Deep Motif-regularized Asymmetric NMF, has been accepted for publication in , Engineering Applications of Artificial Intelligence 2026.
2025
๐๏ธ I attended the “Autumn School: Scientific Machine Learning and Numerical Methods”, at the Centrum Wiskunde & Informatica (CWI), Netherlands, October 27-31, 2025.
๐ฐ Our paper, “A Deep Latent Factor Graph Clustering with Fairness-Utility Trade-off Perspective”, has been accepted for the 2025 IEEE International Conference on Big Data.
๐ฐ Our paper, Distributionally Robust NMF with Self-Paced Learning, has been accepted for publication in Information Sciences journal 2026.
๐ My three Master's students successfully defended their theses in Artificial Intelligence at the Algebraic ML Team, University of Kurdistan, September-October 2025.
๐๏ธ I attended the “SOCN: Stochastic variance-reduced optimization algorithms and applications to federated learning” course, UCLouvain, Belgium, October 7-9, 2025.
๐๏ธ I attended the Systems, Optimization, Control and Networks (SOCN) Workshop, UMONS, Belgium, September 26, 2025.
๐๏ธ I was on the organizing committee of the third workshop on Low-Rank Models and Applications (LRMA 25), Mons, September 11-12, 2025.
๐๏ธ I attended the “PhD School: Machine Learning and Optimization”, at the Centrum Wiskunde & Informatica (CWI), Netherlands, September 2-4, 2025.
๐ฐ Our paper, Encoder-Decoder NMF with ฮฒ-Divergence, has been accepted for publication in Pattern Recognition journal 2026.
๐ฐ Our paper, Instance-wise Distributionally Robust NMF, has been accepted for publication in Pattern Recognition journal 2026. It's my first collaboration with Prof. Nicolas Gillis!
๐๏ธ I attended the “Learning Theory from First Principles” course (Prof. Francis Bach), KU Leuven, Belgium, April 1-3, 2025.
๐๏ธ I attended the Masterclass: “Graphs, Data and AI” (Prof. Jure Leskovec), University of Antwerp, Belgium, March 20, 2025.
๐ค๏ธ I delivered a speech on Deep Matrix Factorizations for Data Representation at the STADIUS Center, KU Leuven, Belgium, February 20, 2025.
2024
๐๏ธ I attended the Graduate School in Systems, Optimization, Control and Networks (SOCN) Study Day, UCLouvain, Belgium, October 29, 2024.
๐๏ธ I attended the Autumn School on Constrained Optimization and Machine Learning, Trier University, Germany, October 9-11, 2024.
๐๏ธ I attended the ALGOPT2024 Workshop on Algorithmic Optimization: Tools for AI and Data Science, UCLouvain, Belgium, August 27-30, 2024.
๐๏ธ My poster was accepted for presentation at the ALGOPT2024 Workshop on Algorithmic Optimization: Tools for AI and Data Science.
๐ฑ I started my PhD in Matrix Theory and Optimization at Polytech MONS, University of Mons, Belgium, June 18, 2024.