PhD Students

Mr. Gyftokostas Nikolaos is a PhD candidate at the Physics Department, at the University of Patras. He received his B.Sc. degree in Physics in 2018 and his M.Sc. degree in Photonics-Lasers in 2020. His M.Sc. thesis is titled: “Classification of extra virgin olive oils via LIBS technique using ns laser pulses combined with machine learning algorithms”. His scientific interest is employing the LIBS technique, mainly for agricultural and enviromental applications, as well as the implementation of machine learning in spectroscopic analysis.

Mr. Stathis Aristeidis is a PhD candidate at the Physics Department at the University of Patras. He received his Bachelor degree from the Univesity of Patras in 2017 and his Master degree from the Univesity of Patras in Photonics-Lasers. His master thesis is titled: “Study of the NLO response and Optical Limiting action of some modified fluorographene derivatives with thiophenol”. His research focuses on the nonlinear optical response of 2D materials like graphene and silecene, nanoribbons, PAHs and other carbon-based nanomaterials.

Mr. Stavrou Michalis is a PhD candidate at the Physics Department at the University of Patras. He received his Bachelor degree from the University of Patras in 2018 and his Master degree from the University of Patras in Photonics-Lasers and Materials. His master thesis is titled: “Nonlinear optical properties of silicene under ns, ps and fs laser pulses”. His research focuses on the nonlinear optical properties of graphenes, silicenes, PAHs and metal nanoparticles, and also on the thermal lensing effects induced in graphene dispersions upon excitation with high repetition rate fs lasers.

Mr. Stefas Dimitrios is a PhD candidate at the Physics Department at the University of Patras. He received his B.Sc. degree in Physics in 2017 and his M.Sc. degree MSc in Photonics-Lasers in 2019. His M.Sc. thesis is titled: “Laser-Induced Breakdown Spectroscopy and Machine Learning Algorithms for polymer classification”. His research is focused on applications of the LIBS technique and the implementation of machine learning algorithms in spectroscopic analysis.