Area of research
Electrical and Electronic Engineering · Signal Processing
Research interest
Research interests include Blind Source Separation Techniques, Organic Light-Emitting Diodes Research, Organic Electronics and Photovoltaics, and Sparse and Compressive Sensing Techniques.
All-fiber mid-infrared supercontinuum generation with high coherence in chalcogenide fiber pumped by 2.8 µm Raman femtosecond solitons
10 W-Level, All-Fiber Supercontinuum Generation From Visible to Mid-Infrared by Broadband Laser Beam Combination in GeO<sub>2</sub>-Core Fiber
Fatigue‐Resistant Conducting Polymer Hydrogels as Strain Sensor for Underwater Robotics
Self-healing electrical bioadhesive interface for electrophysiology recording
High‐Stretchability, Ultralow‐Hysteresis ConductingPolymer Hydrogel Strain Sensors for Soft Machines
Spatiotemporal Sparse Bayesian Learning With Applications to Compressed Sensing of Multichannel Physiological Signals
Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning
Extension of SBL Algorithms for the Recovery of Block Sparse Signals With Intra-Block Correlation
Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG Via Block Sparse Bayesian Learning
Compressed Sensing of EEG for Wireless Telemonitoring With Low Energy Consumption and Inexpensive Hardware
Evolving Signal Processing for Brain–Computer Interfaces
Recovery of block sparse signals using the framework of block sparse Bayesian learning
Sparse Bayesian multi-task learning for predicting cognitive outcomes from neuroimaging measures in Alzheimer's disease