dr.ir. J. Dauwels
Signal Processing Systems (SPS), Department of Microelectronics
Expertise: Machine learning, with applications to autonomous vehicles and biomedical signal processing
Themes: Autonomous sensor systems, Health and WellbeingBiography
Justin Dauwels starts in January 2021 as Associate Professor at TU Delft. Prior to this, he was Associate Professor with the School of Electrical & Electronic Engineering at Nanyang Technological University (NTU), Singapore.
He obtained a PhD degree in electrical engineering at the Swiss Polytechnical Institute of Technology (ETH) in Zurich in December 2005. Next, in 2006-2007 he was a postdoc at the RIKEN Brain Science Institute, Japan (Prof. Shun-ichi Amari and Prof. Andrzej Cichocki), and a research scientist during 2008-2010 in the Stochastic Systems Group (SSG)at the Massachusetts Institute of Technology (MIT), led by Prof. Alan Willsky. He joined NTU in 2010.
His research interests are in Bayesian statistics, iterative signal processing, and computational neuroscience.
Courses
EE4685 Machine learning, a Bayesian perspective
Mathematical foundation for machine learning algorithms, presented from a statistical (Bayesian) and optimization point of view.
EE4C12 Machine learning for Electrical Engineering
Introduction at MSc level
Last updated: 29 Nov 2022
Justin Dauwels
PhD students
MSc students
- Femke Leenen (SPS)
- Jingwen Dun (SPS)
- Junzhe Yin (SPS)
- Ankush Roy (SPS)
- Zipeng Wang (SPS)
- Alan Hamo (SPS)
- Sinian Li (SPS)
- Luuk Bolhuis (SPS)
- Shuoyan Zhao (SPS)
- Jonathan Dijkstra (SPS)
- Doruk Barokas Profeta (SPS)
- Zeineh Bou Cher (SPS)
Alumni
- Chuhan Wang (SPS) (2022)
- Haoran Bi (SPS) (2022)
- Renjie Dai (SPS) (2022)
- Enpu Chen (SPS) (2022)
- Jinchen Zeng (SPS) (2022)
- Zhiyi Wang (SPS) (2022)
- Yanan Hu (SPS) (2022)
- Qi Zhang (SPS) (2022)
- Nan Lin (SPS) (2022)
- Yuanyuan Yao (SPS) (2022)
- Ruben Wijnands (SPS) (2022)
- Pallas Koers (SPS) (2022)
- Yingfeng Jiang (SPS) (2021)