Pablo M. Piaggi

My research focuses on atomistic simulation and machine learning applied to materials science, chemistry, and condensed-matter physics. A central theme in my work is the development of new computational methods for atomistic simulation and their application to problems of technological or fundamental relevance, such as modelling advanced materials, pharmaceuticals, or processes relevant to the environment.

In November 2018, I obtained my PhD in Materials Science under the supervision of Prof. Michele Parrinello at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. After a short stay at ETH Zurich, I moved to Princeton University (USA) supported by a fellowship from the Swiss National Science Foundation (SNSF), where I was later appointed Postdoctoral Research Associate. In 2023, I was selected as an Ikerbasque Research Fellow by Ikerbasque, the Basque Foundation for Science, and moved to CIC nanoGUNE, the nanoscience cooperative research center in Donostia-San Sebastián, Spain. In 2025, I was also awarded the Ramón y Cajal fellowship from the Spanish State Research Agency (AEI). My publications have been cited over 3800 times and my current h-index is 26. A full list of my publications can be found in Google Scholar or arXiv.

I currently lead a team of researchers within the Theory group at nanoGUNE, developing a new line of research on artificial intelligence for atomistic simulation. My research vision for this team is to develop cutting-edge artificial intelligence methods for atomistic simulations of materials and molecules. With our methods, we aim at predicting the properties of materials as well as understanding the atomistic mechanisms behind their transformations with unprecedented accuracy.