Dr. Mohammad Monir Uddin is a researcher in computational mathematics specializing in model order reduction, control theory, numerical linear algebra, and scientific computing, with additional focus on artificial intelligence and deep learning. His work spans the development of efficient algorithms for large-scale sparse descriptor systems, dynamical systems, and optimal control problems. He has contributed to multiple international research groups in Germany and Sweden and has led a range of funded projects in areas such as aircraft wing shape optimization, structure-preserving model reduction, piezo-mechanical systems, and large-scale dynamical system approximation. His research experience includes developing advanced iterative methods, projection techniques, and structure-preserving computational frameworks, while his supervisory work covers model reduction of complex dynamical, biological, and engineering systems. He has delivered numerous talks and poster presentations at international conferences, sharing contributions that advance reduced-order modeling, Krylov subspace methods, and computational techniques for constrained dynamical models, while also teaching and guiding research in applied mathematics and electroweak interaction topics.

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