Nicola MolinariNicola Molinari

Nicola earned a BS and a MS in Physics from the University of Padova (where people of the caliber of Galileo once taught!) in 2013, and spent a year in the UK as part of the ERASMUS scholarship program. He then was awarded a scholarship in the EPSRC Centre for Doctoral Training on Theory and Simulation of Materials at Imperial College London, where he earned a MSc and a PhD in Physics. Nicola joined the MIR lab at its very origin as a Postdoctoral Fellow. His research interests are at the interface between computational condensed matter physics and materials science, and include ionic transport and energy storage, membrane permeation, and mechanical properties of polymers. Among others, he has received the Materials Design Research Prize, the Johnson-Matthey Prize for the Best PhD, and the Blackett Laboratory Industry Club Thesis Prize. Outside the academic walls, his interests include, but are not limited to, cooking, chess, triathlon, and hiking.

Lixin SunLixin Sun

Lixin joined the group as a post-doctoral associate since Oct, 2018. She is trained as a computational material scientist and received her Ph. D degree from the department of Nuclear Science and Engineering in MIT. Her research focuses on elucidating atomistic mechanisms of transport and reactivity at microstructures, i.e. surfaces, interfaces and extended defects, for heterogeneous catalysts and electrochemical materials. She is also working on dimension reduction for enhanced sampling. Outside of research life, she also likes diffusing around the city and operating home furnace for sweets.

Natalya FedorovaNatalya Fedorova

Natalya received her B.S and M.S. in Physics from Ural State University (Russia). She obtained her doctorate from ETH Zurich (Switzerland), where she applied first-principles and Monte Carlo simulations to  investigate the multiferroic properties of perovskite transition metal oxides. Natalya joined MIR as a postdoctoral fellow in January 2019. Currently she is investigating the effects of electron-phonon interaction on the transport properties of thermoelectric materials using first-principles calculations and Boltzmann transport formalism. Natalya has been awarded the Early Postdoc Mobility Fellowship of Swiss National Science Foundation. Apart from science, she enjoys climbing, hiking and guitar playing.

Andrea CepelottiAndrea Cepellotti

Andrea Cepellotti earned a B.S and a M.S. in Physics from University of Trieste (Italy) in 2011. After moving to Switzerland, he received a Ph.D. in Materials Engineering at the École Polytechinque Fédérale de Lausanne (EPFL) in 2016. After a period at the University of California at Berkeley, he is currently a postdoctoral researcher at the Harvard University. His research interests in computational condensed matter physics include thermal transport, surface adsorption and optical properties of solids from first principles. At the MIR group, his research focuses on overcoming the limitations of the Boltzmann transport equation for describing electronic transport in disordered materials and with exotic band structures. His Ph.D. Thesis focused on the study of collective phonon excitations and phonon hydroynamics in low-dimensional materials. He’s a founding developer of AiiDA (, an open source software infrastructure for computational science. He has received the IBM Research Award, the APS Metropolis award, the Young Research Award of the Francophone Carbon Society (SFEC) and the Early Postdoc Mobility Fellowship from the Swiss National Science Foundation (SNF).

NakibProtikNakib Protik

Nakib received his PhD in physics from Boston College in 2019. He is primarily interested in understanding the various aspects of transport in condensed matter. In particular, using Feynman diagrams, density functional theory, and semi-classical transport theories, he studies the mutual drag effect in coupled electron-phonon systems, impurity scattering, various transport regimes, and superconductivity. He is also broadly interested in topological defects and topological phases, machine learning, high-throughput computation, among many other topics. When not working on physics problems, he listens to and plays music, cooks, and watches movies.