Interviews with Giovanni Pizzi, Virginie de Mestral, Xingao Gong, Nicola Marzari

We complete the publication of the interviews filmed during the Psi-k conference in Lausanne in August 2025, where we asked top experts in the discipline to reflect on the state of the art and the future of computational materials science. This time we present the interviews to Giovanni Pizzi, Virginie de Mestral, Xingao Gong, and Nicola Marzari.  All the interviews published so far can be found in this playlist on YouTube. 

Giovanni Pizzi is the group leader of the Materials Software and Data Group in the Laboratory for Materials Simulation at the Paul Scherrer Institute in Villigen, Switzerland. In the third phase of NCCR MARVEL, he has been a project leader for the pillar on Digital Infrastructure of Open Simulations and Data. In this interview, he talks about the importance of the standardization and verification of computer codes in computational materials science. This is more important than ever in the era of machine learning, because the investment on building and training new machine learning models only pays off if the datasets used for training are accurate. He also talks about a crucial legacy of the NCCR MARVEL: the combination of new simulation methods and open-source tools that allow to handle complex computational workflows.

Virginie De Mestral is a doctoral student in Mathieu Luisier’s group at ETH Zurich, and a member of NCCR MARVEL. During her PhD, funded by Innosuisse, she has focussed  on a collaborative project with a Swiss startup to simulate promising materials for applied optoelectronics. In this interview she reflects on how participating in MARVEL as a junior member has opened many doors for her, and on the lessons she’s learned doing research at the interface of academia and industry. She has some key recommendations for other early-career scientists in materials simulation: stay curious, be responsible, and always ask that extra question.

Xingao Gong is a professor of physics at Fudan University in Shanghai, China, where he leads the Institute for Computational Physical Sciences. He is a member of the Chinese Academy of Sciences and a fellow of the American Physical Society.  His research has focussed on explorations of multiferroic materials, magnetic phase transitions, and dynamic simulations of ion and electron behaviors in electrolytes, and has included the development of machine learning potentials for materials simulation.

In his interview, he comments on how AI is changing computational materials science “even too dramatically”, and lays out his expectation that within a decade machine learning tools will make it possible to simulate realistic physical systems like electronic devices, including their manufacturing process. He also describes the current AI boom in China and the strong backing it receives from the government.

Finally, we hear from Nicola Marzari, Director of NCCR MARVEL, Professor and Chair of Theory and Simulation of Materials at the École polytechnique fédérale de Lausanne (EPFL), and head of the Laboratory for Materials Simulations at the Paul Scherrer Institute (PSI), and the next Cavendish Professor of Physics at the University of Cambridge, starting in 2026.

In this interview, filmed during the Psi-k 2025 Conference in Lausanne, he notes that a huge change for the field of computational materials science in the last 10 years has been the interest – and the investments – of major tech companies, now aware that materials and devices can “make or break their future”. He describes the important challenge of increasing the capacity for experiments and automate them to some extent, and more fundamentally of creating computational tools with better predictive accuracy. Looking at the legacy of NCCR MARVEL, that is drawing to a close in 2026, he praises the SNSF funding agency for supporting not only science, but also outreach, technology transfer and equal opportunities.