Current Position, Education, and Research

Marios Mattheakis (Matthaiakis) is a Research Associate at Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) He received his Ph.D. in physics in 2014 from the University of Crete, and obtained his B.Sc and M.Sc from the same institute in 2010 and 2012.

Research Interests

Marios is interested in Applied Computational Science focusing on the intersection of deep learning,  physics, and material science. He develops neural network architectures with embedded physical principles and symmetries  providing data-efficient learning, high predictive accuracy, physics discovery from data, and new methods for solving differential equations. These deep learning approaches  are implemented in a wide range of applications from quantum physics and material engineering to electromagnetics and dynamical systems.

  • Physics-informed machine learning modeling
  • Neural Networks for solving differential equations and eigenvalue problems  
  • Two-dimensional materials and Van der Waals heterostructures
  • Extreme and rare events in disordered systems and random environments 
  • Photonics, plasmonics, light-matter interaction, quantum metamaterials

Extended Curriculum Vitae


Google Scholar       dblp       Semantic    


2015 - 2018  Postdoctoral Research Associate, Harvard John A. Paulson School Of Engineering and Applied Sciences; Advisor: Prof. Efthimios Kaxiras
2018 - present Research Associate, Institute for Applied Computational Science at Harvard John A. Paulson School Of Engineering and Applied Sciences