Office Phone: (+30) 2810 39 4263
Dr. Barmparis Georgios D.
PostDoctoral Fellow


  • 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.


  • 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.


  • 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.


  • 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).
Detection of abnormal left ventricular geometry in patients without cardiovascular disease through machine learning: An ECG‐based approach.
Eleni Angelaki, Maria E. Marketou, Georgios D. Barmparis, Alexandros Patrianakos, Panos E. Vardas, Fragiskos Parthenakis, Giorgos P. Tsironis
J Clin Hypertens, Volume:00, Page:1–11, Year:2021,
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,
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,
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,