Department of Mathematics and Systems Analysis

Current

Lectures, seminars and dissertations

* Dates within the next 7 days are marked by a star.

Markus Hakala (Aalto University)
Estimation of stochastic block models with nodal covariates (MSc thesis talk)
* Monday 19 May 2025,   15:15,   M237
Aalto Statistics Seminar / Lasse Leskelä

Xingyan Quan (Central South University, China)
Matrix-weighted martingale inequalities
* Wednesday 21 May 2025,   10:15,   M3 (M234)
Analysis seminar

Antti Niemi (University of Oulu)
Buckling Stability of Cylindrical Shells: Classical Theory, Nonlinear Analysis, and Design Implications
* Wednesday 21 May 2025,   14:00,   M2 (M233)
Cylindrical shell structures display complex and sensitive buckling behavior that challenges both theoretical modeling and practical design. This presentation revisits classical asymptotic shell buckling theory and examines its numerical treatment, emphasizing nonlinear structural mechanics and the ability of modern computational tools to capture critical loads and deformation modes. The derivation and interpretation of design-oriented knockdown factors are discussed in relation to numerical results. Particular attention is given to the spatial characteristics of buckling modes and more interaction which are essential to accurately assess structural stability through numerical analysis.
Numerical Analysis seminar

Katariina Perkonoja (University of Turku)
Synthetic longitudinal patient data generation: opportunities and limitations
Tuesday 27 May 2025,   15:15,   M2 (M233)
Synthetic longitudinal patient data (LPD) offers a solution to challenges related to data privacy and availability. It involves generating data that mimics real patient information for use in research, development, innovation as well as education. This presentation will explore the concept of synthetic and longitudinal data, review methods for generating and evaluating synthetic longitudinal patient data, and address the limitations and future directions in the field of synthetic LPD generation.

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