
Christos Papadopoulos Filelis
استادیار · Computational Mathematics
Democritus University of Thraceمعرفی
Christos Papadopoulos Filelis is an Assistant Professor at the Department of Electrical and Computer Engineering, Democritus University of Thrace, where he conducts research and teaches courses in computational mathematics and physics. His academic journey began with a Diploma in Electrical and Computer Engineering from Democritus University of Thrace in 2010, followed by a PhD in Numerical Analysis and High Performance Computing from the same institution in 2014.
His research interests span Computational Mathematics, Mathematical and Computational Physics, Numerical Methods, Scientific Calculations, High Performance Computing, and Machine Learning applications in Mathematics and Physics. He has made significant contributions to pre-coordinated iterative methods, multi-grid and multi-level methods, parallel computing, cloud computing, and big data analytics. His work bridges theoretical mathematics with practical computational applications across multiple domains.
Analysis of his recent publications reveals a strong focus on developing advanced computational techniques for solving complex mathematical problems, with particular emphasis on matrix computations, preconditioning methods, and time series analysis. His research demonstrates a consistent trajectory toward more efficient algorithms for high-performance computing environments, with increasing applications in machine learning and environmental sustainability.
Dr. Papadopoulos Filelis has taught undergraduate courses including Physics, Numerical Analysis, Mathematical Software, Scientific Calculations, and Calculus of Changes. He has participated in European (H2020) and National funded projects such as the SFI FinTechNext project (UCC, Ireland), demonstrating his ability to secure competitive research funding.
His work with the Physics Laboratory at Democritus University of Thrace involves developing computational frameworks that integrate theoretical physics with advanced numerical methods. He has collaborated extensively with researchers across Europe, particularly in cloud computing and high-performance computing projects that address real-world computational challenges.
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