Giovanna Tosato

NHR@KIT, Karlsruhe

 

Research Topic

Data-Driven Optimization Strategies for Materials Design.

 

Supervisors

  • Professor Britta Nestler (Karlsruhe Institute of Technology
  • Arnd Hendrik Koeppe, PhD (Karlsruhe Institute of Technology)


Thesis Abstract

My PhD project develops an intelligent framework that helps material scientists steer their studies and reach reliable conclusions with fewer (costly) simulations and experiments. Bridging mathematics and computational materials science, the framework integrates Bayesian active learning, FAIR-aware research data management, interoperability across heterogeneous RDM systems, and scientific visualization to efficiently explore vast search spaces. Proof-of-concept applications from simulations and laboratory battery research demonstrate how the framework accelerates material design by supporting informed, uncertainty-aware decision-making.


Publications

  • Giovanna Tosato et al. “Accelerating battery research with an AI interfacebetween FINALES and Kadi4Mat”. In: arXiv preprint arXiv:2605.00909 (2026).
  • RK Jeela et al. “Enhancing Solid Oxide Fuel Cells Development through Bayesian Active Learning”. In: Advanced Energy Materials (2025), p. 2501216.
     

Conference Presentations

  • NHR Conference 2024 (Contributed Talk & Poster)
  • NHR4CES Community Workshop 2025 (Contributed Talk)
  • NHR Conference 2025 (Poster)