Projects per year
Personal profile
Research profile
Chinhung Chen is enrolled in the PhD program of the Signal Processing System Group at TU/e. His research is focused on wireless communication, bayesian inference, and machine learning
Academic background
Chinhung holds a Bachelor's (2016) and Master's (2018) degree in Atmospheric Science from National Central University, Taiwan. His master's research focused on Microphysics Parameterization, Ensemble-Kalman filter-based Data Assimilation, and Numerical Weather Prediction.
Experience
Chinhung worked as an R&D engineer at the National Chung-Shan Institute of Science and Technology from 2018 to 2022. He specializes in synthetic aperture radar imaging and digital radar receiver design.
Education/Academic qualification
Atmosphere sciences, Master, National Central University
Sept 2016 → Jun 2018
Award Date: 30 Jun 2018
Atmosphere sciences, Bachelor, National Central University
Sept 2012 → Jun 2016
Award Date: 30 Jun 2016
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Collaborations and top research areas from the last five years
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Projects
- 1 Active
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RAISE SPS: Robust AI for SafE (radar) signal processing
Gonzalez Carabarin, L. (Project member), Youn, J. (Project member), Karanov, B. (Project member), Wei, X. (Project member), Fiorio, L. (Project member), Chen, C.-H. (Project member), An, M. (Project member), Belt, H. J. W. (Project member), Manders, T. (Project member), Lima de Oliveira, M. (Project member), Mischi, M. (Project Manager), Overdevest, J. (Project member), Bergmans, J. W. M. (Project member) & Alvarado, A. (Project communication officer)
1/06/21 → 31/05/28
Project: Third tier
Research output
- 2 Conference contribution
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Analysis of Impulsive Interference in Digital Audio Broadcasting Systems in Electric Vehicles
Chen, C.-H., Huang, W.-H., Karanov, B., Young, A., Wu, Y. & van Houtum, W. J., 2024, (Accepted/In press) 44th Symposium on Information Theory and Signal Processing in the Benelux.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access -
On the Robustness of Deep Learning-aided Symbol Detectors to Varying Conditions and Imperfect Channel Knowledge
Chen, C.-H., Karanov, B., van Houtum, W. J., Wu, Y., Young, A. & Alvarado, A., 3 Jul 2024, 2024 IEEE Wireless Communications and Networking Conference, WCNC 2024. Institute of Electrical and Electronics Engineers, 6 p. 10570860Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
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