Alessio Gagliardi

Professor Alessio Gagliardi is an Associate Professor at the TUM School of Computation, Information and Technology, Technische Universität München. His academic career includes a tenure-track position since 2014 and promotion to Associate Professor in 2020. He contributes to the development of the TiberCAD and GDFTB simulation software and integrates machine learning into materials science research.

• Education:
  • Engineering degree from the University of Rome Tor Vergata (Italy)
  • Doctorate in Physics from the University of Paderborn (2007)
  • Postdoctoral research at Bremen Center for Computing Materials and Rome

Research Interests: Prof. Gagliardi’s work focuses on simulating nanostructured devices for energy conversion, including organic semiconductors, perovskite solar cells, and electrochemical systems. His methods span nanoscale (density functional theory, quantum Green’s functions), mesoscale (kinetic Monte Carlo), and macroscopic (drift-diffusion models). Recent efforts emphasize machine learning applications for multiscale modeling and experimental-theoretical integration.

Articles Overview: Recent publications explore machine learning optimization in materials design, nanoscale simulations for energy devices, and advancements in electrocatalysts. Key themes include improving platinum electrocatalyst efficiency, perovskite solar cell stability, and AI-driven predictions for material performance.

Labs/Teams: Active in software development teams for TiberCAD and GDFTB, advancing computational tools for materials science and energy systems.