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
https://orcid.org/0000-0001-6450-1128
Appointments
| 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 |