Profiles

Katerina Nik is an assistant professor of Applied Mathematics and Computational Sciences (AMCS) in the Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division at KAUST. Her work focuses on partial differential equations that describe phenomena in biological growth processes, fluid dynamics, and mechanical engineering. She joined KAUST in 2024 after contributing to research at prominent European institutions.

Prior to joining KAUST, Dr. Nik worked as a principal investigator at the Austrian Academy of Sciences, supported by the APART-MINT Fellowship, which enabled her to lead innovative research in applied mathematics. Before this, she was a postdoctoral researcher at the Delft Institute of Applied Mathematics, TU Delft, where she collaborated with Professor Manuel Gnann's group. She also served as a postdoctoral researcher at the Faculty of Mathematics, University of Vienna, Austria, working with Professor Ulisse Stefanelli from 2020 to 2024.

Earlier in her career, she was a research and teaching assistant at Leibniz University Hannover (LUH), Germany, where she completed her doctorate in mathematics. Her academic contributions during this period focused on nonlinear dynamics and the modeling of complex systems.

Professor Nik works on (nonlinear) partial differential equations that describe phenomena in biological growth processes, fluid dynamics, and mechanical engineering. Additionally, she is interested in modeling with differential equations. In order to solve these problems, Nik employs both applied and pure mathematics methods. Her main research topics include:

• Nonlinear evolution equations and operator semigroups
• Free boundary problems
• Calculus of variations
• Geometric measure theory
• Well-posedness and qualitative properties of solutions
• Nonlinear dispersive waves
• Thin fluid film equations
• Microelectromechanical systems (MEMS)
• Biological growth processes, such as volumetric and surface growth
• Brakke's mean curvature flow

Zhang Zhiwen investigates the long-time behavior and stability of complex kinetic systems, particularly focusing on the phenomenon of Landau damping. He extends the theoretical understanding of Landau damping into 2-species contexts. His research provides critical insights into the stability and dispersive properties of kinetic models, advancing the broader understanding of how these intricate physical systems evolve and stabilize over time.

David Jesus received his Ph.D. from the University of Coimbra in Portugal under the supervision of José Miguel Urbano and Edgard Pimentel in 2023. Then completed 2 years of postdoc in Bologna before joining KAUST in 2025.

Beichen Zhao is currently pursuing his Ph.D. at China University of Petroleum–Beijing. He is also a visiting student in the Applied Mathematics and Computational Science program at King Abdullah University of Science and Technology (KAUST).

Beichen’s research interests include physics-informed neural networks, scientific machine learning, surrogate modeling, subsurface fluid flow, CO₂ enhanced oil recovery, geological carbon storage, and geothermal reservoir simulation.