Nikos KavallarisView profile
Associate Professor
Nikos Kavallaris is an Associate Professor at Karlstad University, specializing in Applied Mathematical Analysis. His research focuses on deterministic and stochastic modeling of biological, ecological, and industrial systems, including chemotaxis, tumor growth, MEMS technology, and uncertainty quantification. He collaborates with institutions like Osaka University and Brown University. He teaches modules such as Optimization and Applied Mathematics for Engineers. Kavallaris holds a PhD from the National Technical University of Athens (2000) and has held academic positions at Aegean University and the University of Chester. He co-organizes the 2024 Equadiff conference’s minisymposium on Nonlocal PDEs. His work bridges theoretical mathematics with applications in biology, engineering, and environmental science. Education: PhD in Applied Mathematics, National Technical University of Athens (2000) Postdoctoral Research: University of Wrocław (EU HYKE project), Osaka University (COE program) Collaborations: Osaka University, Heriot-Watt University, Sorbonne Paris Nord, Brown University Research Interests: Nonlinear PDEs, stochastic modeling in biology/ecology, MEMS device dynamics, and topological data analysis. His work addresses phenomena like tumor growth, DNA methylation, and industrial processes such as ohmic heating and metal welding. He explores quenching dynamics, blow-up solutions, and bifurcation theory in nonlocal models. Publications: Over 50 articles on topics ranging from stochastic MEMS models to cancer immunology, emphasizing nonlinear dynamics and uncertainty quantification. Recent work examines flood exposure in Sweden and immune infiltration patterns in breast cancer. Grants/Awards: Involved in EU Marie-Curie projects and collaborative research initiatives. His contributions span theoretical analysis and application-driven research in interdisciplinary fields. Labs/Teams: Active in international research networks, leading projects on nonlocal PDE applications and mathematical biology.









