Michael Rinderle

Michael Rinderle is a researcher at the Technical University of Munich, affiliated with the TUM School of Computation, Information and Technology. He works under the Associate Professorship of Computational Photonics (headed by Prof. Jirauschek) and the Associate Professorship Simulation of Nanosystems for Energy Conversion (headed by Prof. Alessio Gagliardi). His research focuses on computational modeling of optoelectronic materials and devices, integrating machine learning with multiscale simulations.

Research Interests: Michael specializes in applying machine learning techniques to materials discovery and simulation, particularly for organic semiconductors, perovskite solar cells, and electrocatalytic systems. His work bridges computational methods like kinetic Monte Carlo, density functional theory, and graph neural networks with practical applications in photovoltaics, IoT energy autonomy, and nanoscale device engineering.

Teaching Roles: He contributes to courses including Computational Photonics Laboratory, Python for Engineering Data Analysis, and Simulation of Quantum Devices. His teaching emphasizes practical skills in programming, device simulation, and data visualization for engineering students.

Projects: Involved in DFG e-Conversion clusters (I-III), TUM Innovation Network ARTEMIS, EU Lion-Hearted, and BMWi-funded initiatives, focusing on interfaces, energy conversion, and machine learning-driven materials optimization.