* Dates within the next 7 days are marked by a star.
Konstantinos Bampouras (Aalto University)
Boundary-weighted Fourier inequalities for convex domains
* Today * Wednesday 09 September 2026, 10:15, M3 (M234)
Analysis seminar / Hytönen
Jesse Piispanen
On well-rounded lattices and theta function minimization (MSc thesis presentation)
* Thursday 10 September 2026, 14:15, M3 (M234)
Advisor: Max Forst, Supervisor: Camilla Hollanti
ANTA Seminar / Hollanti et al.
Talal Alrawajfeh (Univ. Helsinki)
TBA (the first meeting of Aalto-Helsinki formalized mathematics seminar)
* Friday 11 September 2026, 13:15, U4062, University of Helsinki main building (Fabianinkatu 33)
Aalto-Helsinki formalized mathematics seminar
Jaime Pardo
Proximal Tensor-Free Approach to Bilinear Inverse Problems
* Tuesday 15 September 2026, 15:15, M1 (M232)
Numerical Analysis seminar
Inka Hirvinen (Umicore Battery Materials Finland)
Uncertainty-Aware Data Mapping and Interpretable Modelling for Complex Process Systems (MSc thesis presentation)
Thursday 17 September 2026, 15:15, Zoom
Battery materials play a significant role in enabling the transition to clean energy
and transportation, thus making the development of new battery materials essential.
The commonly employed trial-and-error approach to battery materials development
is costly, which makes computational modelling an attractive option. In this thesis
we utilize historical data from trial runs to train and compare multiple models to
predict the specific surface area (SSA) of precursor cathode active materials (pCAM).
Subsequently, we employ the best-performing model as a surrogate model to optimize
process parameters, which enables the production of battery materials with desired
properties.
Compared to a previously utilized linear regression model, several models achieve
higher predictive performance. The XGBoost regression model achieves both the
lowest prediction error and the highest computational efficiency, which makes it the
most promising method for SSA prediction. Additionally, we identified a Pareto-
efficient front of optimal process parameter combinations using the trained XGBoost
model to approximate the desired properties.
Lorenzo Zacchini (Aalto University)
TBA (midterm review)
Wednesday 23 September 2026, 10:15, M3 (M234)
Analysis seminar / Hytönen
Jani Onninen (Syracuse University)
TBA
Wednesday 23 September 2026, 11:15, M3 (M234)
Analysis seminar
Juho Korkeala
Exotic mean oscillation and compactness of commutators (Master thesis presentation)
Thursday 24 September 2026, 10:15, M3 (M234)
Analysis seminar (extra meeting) / Hytönen
Aleksis Koski
TBA
Wednesday 07 October 2026, 10:15, M3 (M234)
Analysis seminar
Henri Lahdelma
Midterm review talk
Wednesday 21 October 2026, 10:15, M3 (M234)
Analysis seminar
Wontae Kim (Korea Institute for Advanced Study)
TBA
Wednesday 04 November 2026, 10:15, M3 (M234)
Analysis seminar
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