Dr. Dimitris M. Manias
Dr. dimitris m. manias Postdoctoral Fellow Electrical Engineering And Computer Science

Contact Information
dimitris.manias@ku.ac.ae

Biography

Dr. Dimitris M. Manias received his Ph.D. degree in Multi-scale Analysis from the National Technical University of Athens, Greece, in 2020, after finishing his M.Sc. in Applied Mechanics, in 2013, and M.Eng. in Applied Mathematics and Physical Sciences, in 2011, from the same University. During his Ph.D. studies he embarked in numerous visits to ETH Zurich, KAUST and Khalifa University. In 2021 he joined Khalifa University as a Postdoctoral Fellow.

His work is related to developing and applying algorithmic tools for the analysis of complex multi-scale mathematical models. He uses advanced mathematical tools, related to manifold learning techniques, for the algorithmic construction of reduced models of lower dimension and the acquisition of system-level understanding, by identifying the key subprocesses and the important variables of the models. He has applied these tools for the analysis of models in the field of reacting flows and population dynamics. Currently, he is working on artificial intelligence and blockchain technology with applications to the Metaverse.

His work has led to 18 publications in international high-quality journals and book chapters, active participation in numerous international conferences and to collaborations with groups at prestigious institutions such as KAUST, Sapienza, ETHZ and Princeton.

 


Education
  • Ph.D. Multi-scale Analysis, National Technical University of Athens, Greece, 2020
  • M.Sc. Applied Mechanics, National Technical University of Athens, Greece, 2013
  • M.Eng. Applied Mathematics and Physical Sciences, National Technical University of Athens, Greece, 2011

Teaching
  • Data Analytics (COSC430)

Affiliated Research Institutes/Centers

Research
Research Interests
  • Blockchain technology
  • Machine learning and artificail intelligence
  • Computational algorithms for the asymptotic analysis of complex mathematical models
  • Manifold Learning