About Me
Jeroen Klein Brinke finished his B.Sc in Technical Computer Science at the University of Twente (part of the first wave of TOM students) in 2016 with research being done in wireless sensor networks (flexible sensors in sports applications). In 2018, he received his M.Sc. (cum laude) in Technical Computer Science (specialization: Wireless and Sensor Systems) with research in deep learning and device-free sensing.
His current research still continues this trend, by actively doing research into RF-based device-free sensing in multiple domains and applying deep learning in real-life settings. He is also actively increasing his knowledge in antenna design and radio-wave/signal propagation.
He is also actively involved in his old Bachelor programme, B-TCS, as a mentor for first-year students and participating as a lecturer and supervisor in multiple BSc courses. Since 2019, he also actively helps in and contributes to the M.Sc. course Ubiquitous Computing at the University of Twente.
His current research still continues this trend, by actively doing research into RF-based device-free sensing in multiple domains and applying deep learning in real-life settings. He is also actively increasing his knowledge in antenna design and radio-wave/signal propagation.
He is also actively involved in his old Bachelor programme, B-TCS, as a mentor for first-year students and participating as a lecturer and supervisor in multiple BSc courses. Since 2019, he also actively helps in and contributes to the M.Sc. course Ubiquitous Computing at the University of Twente.
Expertise
Engineering & Materials Science
# Channel State Information
# Convolutional Neural Networks
# Information Analysis
# Predictive Maintenance
# Remote Sensing
# Transfer Learning
Medicine & Life Sciences
# Digital Libraries
# Technology
Organisations
Publications
Recent
Sharma, N.
, Klein Brinke, J.
, van Gemert-Pijnen, L. J. E. W. C.
, & Jansen, L. (2021).
Implementation of Unobtrusive Sensing Systems for Older Adult Care: Scoping Review.
JMIR Aging,
4(4), [e27862].
https://doi.org/10.2196/27862
Klein Brinke, J.
, Chiumento, A.
, & Havinga, P. J. M. (2021).
Personal Hygiene Monitoring Under the Shower Using Wi-Fi Channel State Information. In R-H. Liang, A. Chiumento, P. Pawełczak, & M. Funk (Eds.),
CHIIoT 2021: Workshops on Computer Human Interaction in IoT Applications CEUR.
http://ceur-ws.org/Vol-2996/
Bagave, P., Linssen, J., Teeuw, W.
, Klein Brinke, J.
, & Meratnia, N. (2019).
Channel State Information (CSI) analysis for Predictive Maintenance using Convolutional Neural Network (CNN). In
DATA'19: Proceedings of the 2nd Workshop on Data Acquisition To Analysis (pp. 51-56).
https://doi.org/10.1145/3359427.3361917
Klein Brinke, J.
, & Meratnia, N. (2019).
Scaling Activity Recognition Using Channel State Information Through Convolutional Neural Networks and Transfer Learning. In
AIChallengeIoT ’19: International Workshop on Challenges in Artificial Intelligence and Machine Learning for Internet of Things (pp. 56-62).
https://doi.org/10.1145/3363347.3363362
Klein Brinke, J.
, & Meratnia, N. (2019).
Dataset: Channel State Information for Different Activities, Participants and Days. In
DATA’19: Proceedings of the Second Workshop on Data Acquisition To Analysis (pp. 61-64). ACM Press.
https://doi.org/10.1145/3359427.3361913
UT Research Information System
Google Scholar Link
Affiliated Study Programmes
Bachelor
Master
Courses Academic Year 2021/2022
In the press
- "Making waves with WiFi data" on 4TU Data Community
News on utwente.nl
Contact Details
Visiting Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(building no. 11), room 5032
Hallenweg 19
7522NH Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
5032
P.O. Box 217
7500 AE Enschede
The Netherlands