Lorenzo Pareschi

Lorenzo Pareschi is a Professor and Chair of Applied and Computational Mathematics at the School of Mathematical & Computer Sciences, Heriot-Watt University, Edinburgh, UK. He holds a Ph.D. in Mathematics from the University of Bologna, Italy, and has held visiting professorships at institutions including Georgia Tech, University of Wisconsin-Madison, and Imperial College London. His research focuses on multiscale modeling, numerical methods for nonlinear PDEs, and applications in physics, engineering, and socio-economic systems. Recently, he has explored uncertainty quantification, optimal control, and machine learning. He is a Royal Society Wolfson Fellow (2023) and has served as Head of the Department of Mathematics and Computer Science at the University of Ferrara. He is an associate editor for journals like SIAM Journal on Scientific Computing and Multiscale Modeling & Simulation.

Research interests include hyperbolic and kinetic equations, fluid dynamics, plasma physics, epidemiology, and computational hemodynamics. His work contributes to UN Sustainable Development Goals through applications in healthcare and environmental modeling. He has authored over 200 publications and five books, reflecting his leadership in applied mathematics and interdisciplinary collaboration.

• Education: Ph.D. in Mathematics, University of Bologna (Italy).
• Awards: Royal Society Wolfson Fellowship (2023), Nelder Fellowship (2015), John von Neumann Professorship (2019).
• Roles: Member of SIMAI steering committee, EMS CAIR committee, and editorial boards of key journals.

Research Trends: Recent articles emphasize machine learning integration with kinetic models, plasma control strategies, and multiscale methods for epidemic spread. His work bridges theoretical developments with practical applications in fusion energy, traffic dynamics, and healthcare.

Grants & Advising: Actively supervises PhD students and leads projects on computational methods for complex systems. His grants focus on advancing numerical techniques for multiscale phenomena and uncertainty quantification.

Labs/Teams: Collaborates with global networks in computational mathematics and applied physics, contributing to high-impact journals and conferences.