Category: Seminars and Conferences
State: Archived

Tommaso Lorenzi - University of St. Andrews - NONLINEAR PARTIAL DIFFERENTIAL EQUATIONS MODELLING THE MULTISCALE EVOLUTIONARY DYNAMICS OF CANCER

at 9:30 am - May 16, 2018 - Department of MATHEMATICAL SCIENCES - Aula Buzano

A growing body of research indicates that mathematical modelling can complement experimental cancer research by offering alternative means of interpreting experimental data and by enabling extrapolation beyond empirical observation. This talk deals with mathematical models formulated in terms of nonlinear partial differential equations which can be used to study the multiscale evolutionary dynamics of cancer. Dr. Lorenzi will present a number of results which illustrate how analysis and numerical simulation of these equations can help to uncover fresh insights into the critical mechanisms shaping cancer progression and the emergence of resistance to cytotoxic therapy.

Breve CV/Research:
Since October 2015, Tommaso Lorenzi has been a Research Fellow in Applied Mathematics at the University of St Andrews. He received his PhD in Applied Mathematics in
2013 from the Politecnico di Torino. Upon completion of his PhD, he was awarded a Postdoctoral Fellowship in Mathematics from the Fondation Sciences Mathématiques de Paris (2013) and a Postdoctoral Fellowship in Mathematics for the Life Sciences from the Fondation Mathématique Jacques Hadamard (2014). Tommaso Lorenzi works in Mathematical Biology. The focus of his research is on deterministic models formulated in terms of nonlinear partial differential equations (PDEs), or integro-differential equations (IDEs), and corresponding stochastic individual-based (IB) models. He collaborate interdisciplinary, with cell biologists, immunologists and evolutionary biologists. His current research interests
include: nonlocal multiscale models of phenotypic evolution in cancer cell populations; porous medium-type equations modelling avascular tumour growth and collective cancer cell invasion; nonlocal PDE and IB models of spatial evolutionary games; nonlinear IDEs and PDEs arising in the mathematical modelling of populations structured by behavioural traits.