Office Phone: (+30) 2810 39 4263
Email: barmparis@physics.uoc.gr
Dr. Barmparis Georgios D.
PostDoctoral Fellow

Education

  • 2012, Ph.D. in Materials Science and Technology, Dept. of Materials Science and Technology, University of Crete, Greece.
  • 2008, M.Sc. in Computational Physics, Dept. of Physics, University of Crete, Greece.
  • 2005, B.Sc. in Physics with major in Computational Physics, Dept. of Physics, University of Crete, Greece.

Career

  • 2017 – today, Postdoctoral researcher. Department of Physics, University of Crete, Greece.
  • 2018 – 2019, Postdoctoral researcher. Institute of Electronic Structure and Laser, Foundation of Research and Technology-Hellas, Greece.
  • 2015 – 2016, Postdoctoral scholar. Crete Center for Quantum Complexity and Nanotechnology. Department of Physics, University of Crete, Greece.
  • 2012 – 2015, Postdoctoral scholar. Department of Physics and Astronomy, Vanderbilt University, TN, USA and Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, TN, USA.

Interests

  • Machine Learning in complex systems and Medicine.
  • Dynamical Systems and Chaos.
  • Materials Science and Nanotechnology.
  • Quantum phase transition in strongly correlated systems.
  • Development of scientific software.

Awards/Prizes/Distinctions

  • 2011, “Maria Michail Manassaki" award as the top graduate student of the Department of Materials Science and Technology of the University of Crete, Greece.
  • 2010, Individual HPC-Europa2 grant for a visit in Finland and access to one of Europe’s largest computers (150000 cpu hours).
Estimating the infection horizon of COVID-19 in eight countries with a data-driven approach.
Georgios D. Barmparis, Georgios P. Tsironis
Chaos Soliton Fract, Volume:135, Page:109842, Year:2020, DOI:doi.org/10.1016/j.chaos.2020.109842
Robust prediction of complex spatiotemporal states through machine learning with sparse sensing.
G. D. Barmparis, G. Neofotistos, M. Mattheakis, J. Hizanidis, G. P. Tsironis, E. Kaxiras
Phys. Lett. A, Volume:384, Page:126300, Year:2020, DOI:doi.org/10.1016/j.physleta.2020.126300
Machine Learning With Observers Predicts Complex Spatiotemporal Behavior.
George Neofotistos, Marios Mattheakis, Georgios D. Barmparis, Johanne Hizanidis, Giorgos P. Tsironis, Efthimios Kaxiras
Front. Phys., Volume:7, Page:24, Year:2019, DOI:doi.org/10.3389/fphy.2019.00024