Lieven De Lathauwer is affiliated with KU Leuven in Belgium, specializing in research spanning computer science, mathematics, and engineering. Their work prominently focuses on computational mathematics, computational mechanics, and signal processing, with additional contributions to computational theory, artificial intelligence, and related fields.
The scientist's research covers several main topics, including tensor decomposition and applications, sparse and compressive sensing techniques, blind source separation techniques, matrix theory and algorithms, model reduction and neural networks, advanced neuroimaging techniques and applications, as well as computational physics and Python applications.
Lieven De Lathauwer has published numerous papers in various academic venues. Noteworthy recent publications include:
Frequent co-authors collaborating with De Lathauwer include Nico Vervliet, Eric Evert, Michiel Vandecappelle, Nicolas Gillis, and Ignat Domanov.
They have contributed extensively to leading publication venues with multiple papers published in:
Lieven De Lathauwer has received recognition through awards such as:
Lieven De Lathauwer;Bart De Moor;Joos Vandewalle
Lieven De Lathauwer;Bart De Moor;Joos Vandewalle
Nicholas D. Sidiropoulos;Lieven De Lathauwer;Xiao Fu;Kejun Huang
Andrzej Cichocki;Danilo Mandic;Lieven De Lathauwer;Guoxu Zhou
Lieven De Lathauwer
Lieven De Lathauwer
Lieven De Lathauwer
Laurent Sorber;Marc Van Barel;Lieven De Lathauwer
Lieven De Lathauwer;Dimitri Nion
Lieven De Lathauwer;Bart De Moor;Joos Vandewalle
Marco Signoretto;Quoc Tran Dinh;Lieven Lathauwer;Johan A. Suykens
Lieven De Lathauwer;Bart De Moor;Joos Vandewalle
Lieven De Lathauwer;Joos Vandewalle
Laurent Sorber;Marc Van Barel;Lieven De Lathauwer
Laurent Sorber;Marc Van Barel;Lieven De Lathauwer
Nico Vervliet;Otto Debals;Laurent Sorber;Lieven De Lathauwer
Lieven De Lathauwer
Lieven De Lathauwer;Bart De Moor;Joos Vandewalle
Ignat Domanov;Lieven De Lathauwer
L. de Lathauwer;B. de Moor;J. Vandewalle
Lieven De Lathauwer;Joséphine Castaing
Ignat Domanov;Lieven De Lathauwer
If you think any of the details on this page are incorrect, let us know.
For students studying Mathematics in the USA, exploring related online degrees can open diverse career opportunities. Many professionals complement their quantitative skills with business qualifications to advance in management or finance roles.
Those interested in leadership roles often consider enrolling in the easiest mba program, which offers flexibility without compromising the quality of education. For higher academic and professional achievement, pursuing online dba programs can deepen expertise in business administration with a research focus.
Finance is another popular pathway for math graduates. Affordable options like cheap online masters in finance provide specialized knowledge crucial for roles in investment, analysis, and financial planning.
For those eager to accelerate their career growth, several accelerated mba programs online allow students to complete their degrees faster, combining efficiency with comprehensive learning.
Overall, combining mathematics with these complementary online degrees can enhance job prospects and offer pathways into leadership, finance, and research sectors.
Ming Chi University of Technology
Sungkyunkwan University
University of California, Santa Barbara
University of Aberdeen
JMI Laboratories
Osaka University
Universität Hamburg
Pennsylvania State University
Kyoto University
University of California, San Diego
MIT
University of Padua
Johns Hopkins University
University of Montpellier
University of Leeds
Indiana University
