KU Leuven ESAT STADIUS
STADIUS Center for Dynamical Systems, Signal Processing, and Data Analytics pursues excellence in an explicit and synergistic combination of fundamental and applied research:
With core concepts from linear and multi-linear algebra, statistics, optimization, machine learning, and artificial intelligence, the fundamental research is focused on the development of mathematical engineering tools and numerical algorithms.
Building upon this foundation, the applied research is geared towards putting these tools and algorithms into motion in order to advance the current state of technology across a wide range of relevant application fields, including industrial automation and control, speech and audio signal processing, digital communications, biomedical data analysis and signal processing, bioinformatics and systems biology.
Field of study/sector
- Computer Science & IT
Is part of:
Permanent courses
Tensorlab+
Tool - KU Leuven ESAT STADIUS
Integrating Subspace Identification and Prediction Error Methods
Webinar AI for Times Series with Michel Verhaegen (TU Delft) - Online - VAIA, Flanders AI Research & KU Leuven STADIUS
Kernel Based Transfer Function Estimation with Enhanced Prior Knowledge
Webinar AI for time series with John Lataire - Online - KU Leuven STADIUS & Flanders AI Research & VAIA
Decision Support for the Low Voltage Distribution Grid; the Role of Electricity Consumption Time Series
Webinar AI for time series with Koen Vanthournout - online - KU Leuven STADIUS & Flanders AI Research & VAIA
Statistical Learning of Knowledge from Sequence Data
Webinar AI for Times Series webinar with Nick Harley - Online - VAIA, KU Leuven ESAT Stadius & Flanders AI Research
Distribution-free prediction intervals for time series forecasting
Webinar AI for Times Series with Willem Waegeman - Online - VAIA, KU Leuven ESAT Stadius & Flanders AI Research
Seizure Detection with Wearable Devices and AI
Webinar - VAIA, Flanders AI Research & KU Leuven STADIUS
Past courses
On the Christoffel function and its links with positive polynomials
seminar - Leuven - KU Leuven ESAT STADIUS
Revisiting gray box model learning and Kalman filtering with subspace based model identification
Seminar - Leuven - KU Leuven ESAT STADIUS
Back to the numerical linear algebra roots of polynomials and nonlinear eigenvalue problems
workshop - Leuven - KU Leuven ESAT
Khovanskii Bases for Semimixed Systems of Polynomial Equations
seminar - Heverlee, Leuven - KU Leuven ESAT STADIUS
Some recent developments in multiparameter eigenvalue problems
seminar - Heverlee, Leuven - KU Leuven ESAT STADIUS
Supervised machine learning with tensor network kernel machines
seminar - Heverlee, Leuven - KU Leuven ESAT STADIUS
A new symbolic-numeric method to solve the multiparameter eigenvalue problem
seminar - Heverlee, Leuven - KU Leuven ESAT STADIUS
Experts
Yoeri Uyttendaele
Doctoral Researcher at KU Leuven
Yves Moreau
professor at KU Leuven ESAT STADIUS
Bart De Moor
Voorzitter VAIA (Vlaamse AI Academie), Co-auteur van het Vlaamse Beleidplan Artificiële Intelligentie, Gewoon hoogleraar - KU Leuven
Nithin Govindarajan
KU Leuven ESAT STADIUS
Georges Gielen
KU Leuven ESAT STADIUS
Johan Suykens
KU Leuven ESAT STADIUS
