YIN, Feng

Assistant Professor

Presidential Young Fellow, IEEE Senior Member
Education Background

PhD, MS (Technische Universität Darmstadt)

BS (Shanghai Jiao Tong University)

Research Field
Bayesian machine learning and optimization, statistical signal processing, sensory data fusion, integrated communications, sensing, and localization system
Academic Area
Computer Engineering, Artificial Intelligence and Robotics, Electrical Engineering
Personal Website
https://blsp-group.github.io/
Email
yinfeng@cuhk.edu.cn
Biography

Feng Yin received his B.Sc. degree from Shanghai Jiao Tong University, China, and his M.Sc. and Ph.D. degrees from Technische Universitaet Darmstadt, Germany. From 2014 to 2016, he was a postdoc researcher with Ericsson Research, Linkoping, Sweden. Since 2016, he has been with The Chinese University of Hong Kong, Shenzhen and is currently an assistant professor of the School of Science and Engineering. His research interests include statistical signal processing, Bayesian learning and optimization, and sensory data fusion. He has published more than 40 top-tier journal papers, 50 conferences, and 20 patents/standards. He was a recipient of the Chinese Government Award for Outstanding Self-Financed Students Abroad in 2013 and the Marie Curie Young Fellowship from the European Union in 2014. He was the finalist for the IEEE CAMSAP best paper award in 2013 and received the best paper award of ICSINC conference in 2022. He has served as Associate Editor for the Elsevier Signal Processing Journal and currently serving as the Associate Editor for the IEEE Transactions on Signal Processing. He is an IEEE senior member and a core member of the IEEE Machine Learning and Signal Processing (MLSP) technical committee and the IEEE SPS scholarship committee.

Academic Publications
  1. L. Cheng, Feng Yin (Co-first author, equal contribution, Corresponding author), Sergios Theodoridis, Tsung-Hui Chang, “Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling”,  IEEE Signal Processing Magazine, vol. 39, no. 6, pp. 18-52, Nov. 2022. (ESI-Highly Cited Article, ESI-Hot Article)
  2. Y. Li, Z. Lin, Feng Yin (Corresponding Author), M. M. Zhang, “Preventing Model Collapse in Gaussian Process Latent Variable Models”, accepted by International Conference on Machine Learning (ICML)-2024, Vienna Austria, July 2024. pp.1-31.
  3. Y. Dai, W. Yan, Feng Yin (Corresponding author), “Graphical Multioutput Gaussian Process with Attention”, accepted by International Conference on Learning Representations (ICLR)-2024 Spotlight (~ top 5%), Vienna Austria, May 2024.
  4. T. Zhang, Feng Yin (Corresponding author), Z.-Q. Luo, “Fast Generic Interaction Detection for Model Interpretability and Compression”, in Proc. International Conference on Learning Representations (ICLR), April 2022.
  5. J. Gao, D. Wu, Feng Yin (Corresponding author), Q. Kong, L. Xu and S. Cui, “MetaLoc: Learning to Learn Wireless Localization”, IEEE Journal on Selected Areas in Communications, vol. 41, no. 12, pp. 3831-3847, Dec. 2023. (ESI-Highly Cited Article, ESI-Hot Article)
  6. Y. Xu, Feng Yin (Corresponding author), W. Xu, J. Lin and S. Cui, “Wireless Traffic Prediction with Scalable Gaussian Process: Framework, Algorithms, and Verification”, IEEE Journal on Selected Areas in Communications, vol. 37, no. 6, pp. 1291-1306, June 2019.
  7. Feng Yin, Z.Lin, Q.Kong, Y.Xu, D.Li, S.Theodoridis, S.Cui,“FedLoc: Federated Learning Framework for Data-Driven Cooperative Localization and Location Data Processing”, (long tutorial paper), IEEE Open Journal of Signal Processing, vol. 1, pp. 187-215, November 2020.
  8. Feng Yin and F. Gunnarsson, “Distributed Recursive Gaussian Processes for RSS Map Applied to Target Tracking”, IEEE Journal of Selected Topic in Signal Processing, vol. 11, issue 3, pp.492-503, April 2017.
  9. Z. Lin, Y. Sun, Feng Yin (Corresponding Author) and A. H. Thiery, “Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference”, IEEE Transactions on Signal Processing, October 2024, doi: 10.1109/TSP.2024.3448291. 
  10. M. Zhang, Z. Wang, Feng Yin, and X. Shen, "Distributed Scaled Proximal ADMM Algorithms for Cooperative Localization in WSNs”, IEEE Transactions on Signal Processing, vol. 71, pp. 33123327, September 2023.
  11. D. Jin, Feng Yin (Corresponding Author), A. M. Zoubir and H. C. So, "Exploiting Sparsity of Ranging Biases for NLOS Mitigation”, IEEE Transactions on Signal Processing, vol. 69, pp. 3782-3795, 2021.
  12. Feng Yin, L. Pan, T. Chen, S. Theodoridis, Z.-Q. Luo “Linear Multiple Low-Rank Kernel based Stationary Gaussian Processes Regression for Time Series”, IEEE Transactions on Signal Processing, vol. 68, pp. 5260-5275, October 2020.
  13. D. Jin, Feng Yin (Corresponding Author), C. Fritsche, A. M. Zoubir, F. Gustafsson, "Bayesian Cooperative Localization Using Received-Signal-Strength with Unknown Path Loss Exponent: Message Passing Approaches”, IEEE Transactions on Signal Processing, Vol.68, pp.1120-1135, December 2019.
  14. Y. Zhao, C. Fritsche, G. Hendeby, Feng Yin (Corresponding Author), F. Gunnarsson, "Cramer-Rao Bounds for Filtering based on Gaussian Process State-Space Models”,  IEEE Transactions on Signal Processing, vol. 67, issue 23, pp. 1197-1899, December 2019.
  15. Feng Yin, Y. Zhao, F. Gunnarsson, F. Gustafsson, "Received-Signal-Strength Threshold Optimization Using Gaussian Processes”, IEEE Transactions on Signal Processing, vol. 65, no.8, pp. 2164-2177, April 2017.
  16. Feng Yin, C. Fritsche, F. Gustafsson and A. M. Zoubir, "Cooperative Localization in WSNs Using Gaussian Mixture Modeling: Distributed ECM algorithms”, IEEE Transactions on Signal Processing, vol.63, no.6, pp. 1448-1463, March 2015.
  17. Feng Yin, C. Fritsche, F. Gustafsson and A. M. Zoubir, “Cooperative Localization in WSNs Using Gaussian Mixture Modeling: Distributed ECM algorithms”, IEEE Transactions on Signal Processing, vol.63, no.6, pp. 1448-1463, March 2015.
  18. Feng Yin, C. Fritsche, F. Gustafsson and A. M. Zoubir, "EM- and JMAP-ML Based Joint Estimation Algorithms for Robust Geolocation in LOS/NLOS Environment”, IEEE Transactions on Signal Processing, vol.62, no.1, pp. 168-182, January 2014.
  19. Feng Yin, C. Fritsche, F. Gustafsson and A. M. Zoubir, “TOA Based Robust Wireless Geolocation and Cramér-Rao Lower Bound Analysis in Harsh LOS/NLOS Environments”, IEEE Transactions on Signal Processing, vol. 61, no. 9, pp. 2243-2255, May 2013.
  20. Feng Yin, C. Debes and A. M. Zoubir, "Parametric Waveform Design using Discrete Prolate Spheroidal Sequences for Enhanced Detection of Extended Targets”, IEEE Transactions on Signal Processing, vol. 60, no. 9, pp. 4525-4536, September 2012