Gjesteforelesninger og seminarer - Side 5

Anders Malthe-Sørenssen is a professor of physics. His research interests spans computational and statistical physics, the physics of geological processes, artificial intelligence and neuroscience. He has systematically studied how the frictional behavior of materials may depend on the contact history, for example, by demonstrating that the static coefficient of friction may depend on the acceleration of a block while coming to rest. More recently, he has addressed nano-scale frictional behavior for single contacts, sheets and metamaterials.

Olav Nikolai Breivik is a researcher at the Norwegian Computing Center, where he mainly works on applying statistical methodology to marine science, as well as other projects in applied statistics. He earned his Ph.D. in statistics from the University of Oslo under the supervision of Ida Scheel, Geir Storvik, Arne Bang Huseby and Bent Natvig.

C*-seminar by David Jaklitsch (University of Oslo).

Ivar Svalheim Haugerud is a postdoctoral researcher at the Department of Mathematics, University of Oslo. His research interests lie at the interface of non-equilibrium thermodynamics, soft matter, and chemical physics. In his PhD work, he studied how simple chemical systems driven far from equilibrium can give rise to emergent, life-like behavior, with a particular focus on non-dilute mixtures, phase separation, and active droplets. Using a non-equilibrium thermodynamic framework, his work explored the interplay between phase separation and phenomena such as excitability, self-sustaining oscillations, oligomer sequence selection, and the replication of sequence information, with the aim of identifying minimal physical mechanisms relevant to the emergence of life.

Abstract: See part I.

Christophe Eloy is a Professor of Fluid Mechanics at Centrale Marseille and carries out his research at the IRPHE institute in Marseille. His research explores a wide range of fundamental problems in fluid and solid mechanics—from fluid–structure interactions and hydrodynamic instabilities to animal locomotion, aeroelasticity, rotating flows, and even plant biomechanics—using a blend of theory, experiments, and numerical simulations.

Since Ellingsrud and Peskine showed that there is an upper bound on the degree of smooth surfaces not of general type in P^4, there have been efforts to find them. I will give a survey of different methods of construction, and a list of the kind of surfaces known so far, reporting also on joint work with Hirotachi Abo and Frank-Olaf Schreyer to write a Macaulay2 package that produces equations of examples of each kind.

To each matroid we associate a class in the Chow ring of the Grassmannian. We develop a new combinatorial approach for computing these Chow classes, by first focusing on snake matroids and then extending our results via valuativity to Lattice path matroids, and further to any matroid. Our main contribution identifies the Poincaré dual of the Chow class of a snake matroid with a specific ribbon Schur function, providing an explicit formula for its coefficients in the Schubert basis as the number of standard Young tableaux of a given shape with a prescribed descent set. As consequences, we recover and simplify classical results such as Gessel--Viennot’s enumeration of permutations with fixed descent sets, and formulas for the volume of lattice path matroids. Furthermore, we use our results to show that certain Schubert coefficients are positive for all connected paving matroids.

Rebecca Killick received their PhD degree in Statistics from Lancaster University, where they hold Professor and Director of Research positions. In 2019 they were the first UK recipient of the “Young Statistician of the Year” award from the European Network for Business and Industrial Statistics which recognizes the work of young people in introducing innovative methods, promoting the use of statistics and/or successfully using it in daily practice. Rebecca sees their research as a feedback loop, being inspired by problems in real world applications, creating novel methodology to solve those problems and then feeding these back into the problem domain. Their primary research interests lie in development of novel methodology for the analysis of univariate and multivariate nonstationary time series models. This covers many topics including developing models, model selection, efficient estimation, diagnostics, clustering and prediction. Rebecca is highly motivated by real world problems and has worked with data in a range of fields including Bioinformatics, Energy, Engineering, Environment, Finance, Health, Linguistics and Official Statistics. Rebecca is passionate about ensuring the availability and accessibility of research in the form of open-source software. As part of this they advocate to the statistical community the importance of recognition of research software as an academic output, are co-Editor in Chief of the Journal of Statistical Software and a member of the rOpenSci statistical software peer review board.

The Section 4 seminar for Spring 2026 will be held on Fridays at 10.15 am in room 1120.

William R.P. Denault is a researcher at OCBE-OUS where he focuses on statistical genetics. He got his Ph.D. at the University of Bergen under the supervison of Haakon Gjessing and Astanand Jugessur.

Ivar A. Seierstad is a researcher at the Norwegian Meteorological Institute (MET Norway), where he leads the development of weather forecasts for the public weather service Yr. He received his PhD in meteorology from the University of Bergen in 2008.

Touqeer Ahmad recently joined the Department of Mathematics at UiO as a postdoctoral research fellow under the DSTrain–MSCA program. His project will focus on the stochastic modelling of natural processes. Before that, he was a postdoctoral research fellow at the Institut Denis Poisson, Université d’Orléans, France, from May 2025 to October 2025. There, he worked on the missing data problem in high-dimensional environmental time series as part of the JUNON project. Prior to that, he also held a postdoctoral position at ENSAI, France, from May 2023 to April 2025, where he worked on machine learning and data mining of extreme values in massive data under a prestigious Région Bretagne research grant. He earned a PhD in statistics with the Doctor Europaeus Label in June 2023 from the Department of Statistical Sciences at the University of Padova, Italy. His doctoral research focused on the modeling of discrete extreme values.