Content available in repository
Content available in repository
P.O. Box 513, Department of Methematics and Computer Science
5600 MB Eindhoven
Netherlands
The Statistics group develops and compares data-analytical methods for analyzing and sampling complex structured correlated data sets. It includes parameter estimation, model fitting, latent variable models, mixed models, missing data, statistical process control, survival & reliability theory, time series analysis, and statistical learning methods.
One of the central themes is the analysis of high-dimensional temporal data sets and other large data sets. The group actively explores new research lines in Data Science and maintains many strong ties with industry, including biopharmaceutical companies, chemical industry, medical centers and international research institutes.
The Statistics group develops and compares data-analytical methods for analyzing and sampling complex structured correlated data sets.
Framingham Heart Study A long-term longitudinal data set on more than 5000 participants (started at 1948) has been brought to the TU/e to collaborate with Boston University on new statistical methods.
Strong collaboration with the Academic partners of Maelstrom Research a leading international institute on harmonization of data from multiple cohort studies.
Industrial collaboration with pharmaceutical industry on validation and implementation of rapid microbiological methods to test medicinal products and processes.
Continuous Personal Health as part of the Philips flagship Data Science , is currently developing new methods for monitoring heart characteristics and sleep.
We are leading a Big Data & Reliability Platform together with industrial partners.
Person: Prom. : doctoral candidate (PhD)
Person: OWP : University Teacher / Researcher
Person: HGL : Professor, HGL : Professor
Research output: Contribution to journal › Article › Academic › peer-review
Research output: Contribution to journal › Article › Academic › peer-review
Research output: Book/Report › Inaugural/farewell speech › Popular
Zhan, Z. (Creator), Harvard Dataverse, 2020
DOI: 10.7910/dvn/4uomeh, https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/4UOMEH
Dataset
Zhan, Z. (Creator), de Bock, G. H. (Creator) & van den Heuvel, E. R. (Creator), Figshare, 18 Nov 2022
DOI: 10.6084/m9.figshare.21582023
Dataset
Zhan, Z. (Creator), de Bock, G. H. (Creator) & van den Heuvel, E. R. (Creator), Figshare, 18 Nov 2022
DOI: 10.6084/m9.figshare.21582020
Dataset
Piet Daas (Speaker)
Activity: Talk or presentation types › Keynote talk › Scientific
Marco Puts (Speaker) & Piet Daas (Speaker)
Activity: Talk or presentation types › Keynote talk › Professional
Piet Daas (Speaker) & Marco Puts (Speaker)
Activity: Talk or presentation types › Keynote talk › Professional
4/02/22
1 item of Media coverage
Press/Media: Expert Comment
28/12/21
1 item of Media coverage
Press/Media: Expert Comment
21/12/21 → 22/12/21
3 items of Media coverage
Press/Media: Expert Comment
Supervisor: Castro, R. M. (Supervisor 1) & Stoepker, I. V. (Supervisor 1)
Student thesis: Bachelor
Supervisor: Castro, R. M. (Supervisor 1)
Student thesis: Master
Supervisor: van den Heuvel, E. R. (Supervisor 1) & Regis, M. (Supervisor 2)
Student thesis: Master