The Computational Science and Machine Learning Laboratory

Welcome to the Computational Science and Machine Learning Laboratory (CSML-RTEU). We are an interdisciplinary research group working across several complementary research domains, including computational materials science, condensed matter physics, density functional theory-based simulations, two-dimensional materials, photocatalysis, renewable energy technologies, and machine learning applications.

Our research focuses on the theoretical investigation of low-dimensional materials and their electronic, optical, and photocatalytic properties, with particular emphasis on energy-related applications such as water splitting and next-generation catalyst design. In parallel, CSML conducts data-driven studies in renewable energy systems, where graduate students in Electrical and Electronics Engineering develop machine learning-based approaches for forecasting, performance estimation, optimization, and intelligent decision-making.

By bringing together physics-based modeling, artificial intelligence, and electrical-electronics engineering perspectives, CSML aims to contribute to both fundamental scientific understanding and sustainable energy technologies.

We invite you to meet our team, explore our research projects, and connect with us for academic collaboration opportunities.