Rate My Professor Kevin Rossi

With a background including postdoctoral research at the École Polytechnique Fédérale de Lausanne, Rossi has authored numerous influential publications in computational materials science, catalysis, and nanotechnology. Key works include 'Alloying as a Strategy to Boost the Stability of Copper Nanocatalysts during the Electrochemical CO2 Reduction Reaction' (Journal of the American Chemical Society, 2023), 'Shaping Copper Nanocatalysts to Steer Selectivity in the Electrochemical CO2 Reduction Reaction' (Accounts of Chemical Research, 2022), 'Well-Defined Copper-Based Nanocatalysts for Selective Electrochemical Reduction of CO2 to C2 Products' (ACS Energy Letters, 2022), 'Data-driven simulation and characterisation of gold nanoparticle melting' (Nature Communications, 2021), 'Uncertainty estimation for molecular dynamics and sampling' (The Journal of Chemical Physics, 2021), and recent contributions such as 'Uncertainty in the era of machine learning for atomistic modeling' (Digital Discovery, 2025) and 'Machine Learning-Based Predictions of Henry Coefficients for Long-Chain Alkanes in One-Dimensional Zeolites: Application to Hydroisomerization' (The Journal of Physical Chemistry C, 2025). His research has garnered significant recognition through citations exceeding 1400 and invitations to speak on critical raw materials at events across Europe. Rossi has also secured grants for collaborative networks on materials security and climate transition.