Prior to coming to Boise State in 2010, Dr. Hao Chen worked at Syracuse University as a research assistant professor. He has a Ph.D. in Electrical Engineering from Syracuse University and master’s and bachelor’s degrees in Electrical Engineering from the University of Science and Technology of China. Dr. Chen’s research interests include noise-enhanced signal processing (NESP), stochastic resonance (SR), distributed inference, detection and estimation, image processing and cognitive radio. He recently received the All University Doctoral Prize at Syracuse University. Dr. Chen has many professional affiliations, including membership in the Institute of Electrical and Electronics Engineers (IEEE) and American Society for Engineering Education.
Articles and Conference Proceedings
Performance Limits of Compressive Sensing-Based Signal Classification (with Thakshila Wimalajeewa and Pramod K. Varshney), IEEE Transactions on Signal Processing (2012)
Most of the recent compressive sensing (CS) literature has focused on sparse signal recovery based...
A New Framework for Distributed Detection with Conditionally Dependent Observations (with Biao Chen and Pramod K. Varshney), IEEE Transactions on Signal Processing (2012)
Distributed detection with conditionally dependent observations is known to be a challenging problem in decentralized...
Nonparametric Copula Density Estimation in Sensor Networks (with Leming Qu and Yicheng Tu), Seventh International Conference on Mobile Ad-hoc and Sensor Networks (MSN) (2011)
Statistical and machine learning is a fundamental task in sensor networks. Real world data almost...
Spatial Whitening Framework for Distributed Estimation (with Swarnendu Kar and Pramod K. Varshney), 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) (2011)
Designing resource allocation strategies for power constrained sensor network in the presence of correlated data...
An Image Fusion Approach Based on Markov Random Fields (with Min Xu and Pramod K. Varshney), IEEE Transactions on Geoscience and Remote Sensing (2011)
Markov random field (MRF) models are powerful tools to model image characteristics accurately and have...
Patents
Optimized Stochastic Resonance Method for Signal Detection and Image Processing (with P. K. Varshney and J. H. Michels) (2010)
Apparatus and method for improving the detection of signals obscured by noise using stochastic resonance...