zhilin zhang

ZHILIN ZHANG "Man cannot discover new oceans unless he has the courage to lose sight of the shore."

PERSONAL INFORMATION Phone: Homepage:

1-858-352-8231 https://sites.google.com/site/researchbyzhang/

Email: Visa Status:

[email protected] US Green Card Holder

RESEARCH AREAS (ALGORITHMS) Signal Processing:

Biomedical Signal Processing: Machine Learning:

Wearable Sensing: Time Series Analysis:

● ● ● ● ● ● ● ● ● ● ●

Statistical Signal Processing Adaptive Signal Processing Denoising & Artifact Removal PPG Signal Processing PCG Signal Processing EMG Signal Processing Supervised Learning Bayesian Inference Predictive Modeling Sensor Data Fusion Forecasting

● ● ● ● ●

Compressed Sensing/Sparse Signal Recovery Blind Signal Separation Signal Decomposition EEG Signal Processing ECG Signal Processing

● Unsupervised Learning ● High-Dimensional Sparse Regression ● Motion Artifact Removal ● Abnormality and Motif Detection

RESEARCH AREAS (APPLICATIONS) Wearable Healthcare: Smart Home:

● ● ● ●

Vital Signs Acquisition & Analysis Low Power Data Compression Internet of Things (IoT) Control of Smart Devices

● Inertial Sensor Signal Processing ● Gesture and Activity Recognition ● Non-intrusive Appliance Load Monitoring

SKILLS Big Data Tools: Database: Software: Hardware:

● ● ● ●

R SQL MATLAB Arduino

● Python

● Spark

● JAVA ● C/C++ ● Raspberry Pi

● Hadoop ● Android Programming

EDUCATION 09/2007 -- 12/2012

Ph.D. in Electrical Engineering University of California, San Diego -- California, USA Dissertation: Sparse Signal Recovery Exploiting Spatiotemporal Correlation

Advisor: Prof. Bhaskar D. Rao

09/2002 -- 06/2005

M.S. in Electrical Engineering University of Electronic Science and Technology of China -- China Thesis: Independent Component Analysis with Applications to Biomedical Engineering

09/1998 -- 06/2002

B.S. in Automatics University of Electronic Science and Technology of China -- China

1 Zhilin Zhang | Updated: Oct. 2015

ACADEMIC AND INDUSTRIAL R&D EXPERIENCE 02/2015 -- Current 01/2013 -- 01/2015

Manager, Staff Research Engineer Senior Research Engineer Samsung Research America -- Richardson, TX, USA Finished Projects:

 PPG-Based Heart Rate Monitoring for Smart-Watch  Using PPG signals and acceleration signals recorded by smart-watch, developed algorithms to real-time estimate heart rate with accuracy higher than the project-required accuracy by more than 4%;  Invented novel motion artifact removal methods which have low computational load and are effective for different human activities (walking, running, cycling, jumping, dancing, etc.), different skin-colors, and different sweat-levels;  Shortened the algorithm development phase by 3 months;  Received Samsung Achievement Award;  A paper published in IEEE Transactions on Biomedical Engineering was ranked as the "most cited article in recent years" in this journal.  Inertial Sensor Signal Processing for Smart-Ring  Using acceleration and gyroscope signals recorded by smart-ring, developed algorithms to control remote devices through hand gestures with accuracy higher than the project-required accuracy by 2%;  Invented algorithms for noise reduction, artifact removal, navigation, gesture signal segmentation, gesture classification, and calibration on inertial sensor data;  Finished the algorithm development phase in just 12 weeks;  Received Samsung Achievement Award;  Signal Processing for Smart Glove  Using surface EMG signals, developed algorithms to detect finger movements, which were used in smart-glove for augmented reality;  Invented algorithms for noise reduction, artifact removal, signal segmentation, and parameter estimation on EMG signals;  Signal Processing for Smart-Glass  Using EOG signals recorded by smart-glass, developed algorithms to detect eye movements (left, right, up, and down) to realize some commands used in smart-glass applications with accuracy higher than the projectrequired accuracy by 10%;  Signal Processing for Brain-Computer Interfaces  Developed EEG-based signal processing algorithms for brain-computer interfaces (SSVEP and P300 modes) to control remote devices with required accuracy of 90%+;  Results were reported by MIT Technical Review, IEEE Spectrum, CNN, and other 30+ technical media  Appliance Load Monitoring and energy service in Smart-Home  Invented novel algorithms for non-intrusive appliance load monitoring and real-time energy usage estimation for air-conditioner, dryer, oven, electric vehicle, refrigerator, and other appliances in residual houses with accuracy higher than the project-required accuracy by 21% - 36%;  Invented an energy management system for smart-vent to save energy consumption through indoor-location and human activity detection;  Shortened the algorithm development phase by 3 months;  Received Samsung Achievement Award  Phase Noise Mitigation for mmWave Wireless Communication Systems  Invented smoothness-based algorithms to mitigate phase noise in single-carrier wireless communication systems with performance higher than the project requirement by 9 dBc;  Invented sparsity-based algorithms to mitigate phase noise in OFDM systems with performance higher than the project requirement by 4 dBc;  Received Samsung Achievement Award

Adjunct Professor School of Computer Science and Engineering University of Electronic Science and Technology of China -- Chengdu, Sichuan, China 2 Zhilin Zhang | Updated: Oct. 2015

01/2015 -- Current

 Mentor graduate students on wearable health monitoring via weekly teleconference  Give short-term lectures during yearly visiting

09/2007 -- 12/2012 Research Assistant Digital Signal Processing Lab, University of California, San Diego -- La Jolla, California, USA Advisor: Prof. Bhaskar D. Rao Research Description:  Sparse Signal Recovery & Compressed Sensing  Proposed correlation-based sparse signal recovery/compressed sensing frameworks, first revealing sparsity is not the only information to solve the sparse signal recovery/compressed sensing problems in noisy environment  Sparse Bayesian Learning for High-Dimensional Regression  Invented Bayesian learning algorithms for high-dimensional regression problems and underdetermined sparsityconstrained regression problems by exploiting structured sparsity of regression coefficients and by adaptively learning correlation structures of regression coefficients  Wearable/Wireless Health Monitoring  Proposed correlation-based compressed sensing frameworks of low power data compression for wearable health monitoring, with robustness to noise and artifacts commonly incurred in wearable recordings  Proposed compressed sensing-based data transmission frameworks for wearable fECG monitoring and wearable EEG monitoring, which have the highest performance among state-of-the-art algorithms  Research Outputs  Main results were published in top journals and conferences including IEEE Trans. Signal Processing, IEEE Journal of Selected Topics in Signal Processing, IEEE Trans. Biomedical Engineering, IEEE Trans. Neural Systems and Rehabilitation Engineering, CVPR, ICASSP, etc.  Two papers were ranked as the "Most Cited Articles Published in 2013 & 2014 in IEEE Trans. on Biomedical Engineering" (ranked No.1 and No.2)  Total citations over 1000 times as of September 2015

06/2010 -- 12/2012 Research Assistant Swartz Center for Computational Neuroscience, University of California, San Diego -- California, USA Work with: Prof. Tzyy-Ping Jung & Prof. Scott Makeig Research Descriptions:    

EEG-Based Drowsiness Detection and Prediction for Driver's Safety EEG Source Localization Brain-Computer Interfaces Research Outputs  Main results were published in the top journal Proceedings of the IEEE

06/2011 -- 09/2011, 06/2012 -- 09/2012 Visiting Scholar Indiana University School of Medicine -- IN, USA Work with: Prof. Li Shen, Prof. Shiaofen Fang, & Prof. Andrew Saykin Research Descriptions:  Large-Scale Data Mining for Identifying Multi-Modal Biomarkers and Outcome Prediction  Proposed novel sparse regression algorithms to predict cognition levels of patients with Alzheimer's Disease from their neuroimaging measures, and to discover biomarkers from these measures; performance is higher than state-of-the-art algorithms by 5% - 35% on various benchmark datasets  Initiated the first study in this area that jointly using multiple correlation structures, sparsity structures, and nonlinearity structures in sparse regression models  Research Outputs  Main results were published in top journals and conferences including IEEE Trans. Medical Imaging and CVPR

Visiting Scholar Computer Science Department, Shanghai Jiao Tong University -- Shanghai, China Work with: Prof. Li-Qing Zhang Research Descriptions: 3 Zhilin Zhang | Updated: Oct. 2015

09/2005 -- 06/2007

 Blind Source Separation for artifact removal in EEG signals  Fetal ECG Signal Extraction from Maternal Abdominal Recordings  Research Outputs  Main results were published in machine learning journal Neurocomputing with citations over 200 times  A prototype won the Second Prize in College Student Entrepreneur Competition

WORK EXPERIENCE (NON- R&D) Manager (part time)

09/2003 -- 07/2005

New Century Bookstore for Postgraduate Student Entry Exam -- Chengdu, China  Responsible for strategic planning and marketing  Revenue increased by approximately 300% in two years

PUBLICATIONS Total citations: 1050+ times | h-index: 16 (from Goolge-Scholar as of October 2015)

Journal Publications (* indicates corresponding author; # indicates equal contribution) 2015

2014

[J20]

Zhilin Zhang, “Photoplethysmography-Based Heart Rate Monitoring in Physical Activities via Joint Sparse Spectrum Reconstruction”, IEEE Trans. on Biomedical Engineering, vol.62, no.8, pp.1902--1910, August 2015

[J19]

Zhilin Zhang*, Zhouyue Pi, Benyuan Liu, “TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type Photoplethysmographic Signals During Intensive Physical Exercise”, IEEE Trans. on Biomedical Engineering, vol. 62, no. 2, pp. 522-531, February 2015 [Most Cited Articles Published in Recent Years in This Journal] 21 Citations Since Published in Feb. 2015

[J18]

Biao Sun, Zhilin Zhang*, “Photoplethysmography-Based Heart Rate Monitoring Using Asymmetric Least Squares Spectrum Subtraction and Bayesian Decision Theory”, IEEE Sensors Journal, vol. 15, no. 12, pp. 7161-7168, 2015

[J17]

Yangsong Zhang, Benyuan Liu, Zhilin Zhang*, “Combining Ensemble Empirical Mode Decomposition with Spectrum Subtraction Technique for Heart Rate Monitoring Using Wrist-Type Photoplethysmography”, Biomedical Signal Processing and Control, vol.21, pp.119--125, 2015

[J16]

Zhilin Zhang, “Undergraduate Students Compete in the IEEE Signal Processing Cup: Part 3”, IEEE Signal Processing Magazine, vol.32, no.6, 2015

[J15]

Kin-Man Lam, Carlos Oscar S. Sorzano, Zhilin Zhang, Patrizio Campisi “Undergraduate Students Compete in the IEEE Signal Processing Cup: Part 1”, IEEE Signal Processing Magazine, vol.32, no.4, pp.123--125, 2015

[J14]

Zhilin Zhang*, Tzyy-Ping Jung, Scott Makeig, Zhouyue Pi, Bhaskar D. Rao, “Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals”, IEEE Trans. on Neural Systems and Rehabilitation Engineering, vol. 22, no. 6, pp.1186-1197, 2014

[J13]

Jing Wan , Zhilin Zhang , Bhaskar D. Rao, Shiaofen Fang, Jingwen Yan, Andrew Saykin, Li Shen, “Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlationand Nonlinearity-Aware Sparse Bayesian Learning”, IEEE Trans. on Medical Imaging, vol. 33, no. 7, pp.1476-1788, 2014 (# Equal Contribution)

#

#


2013

[J12]

Benyuan Liu, Zhilin Zhang*, Gary Xu, Hongqi Fan, Qiang Fu, “Energy-Efficient Telemonitoring of Physiological Signals via Compressed Sensing: A Fast Algorithm and Power Consumption Evaluation”, Biomedical Signal Processing and Control, vol.11, pp.80-88, 2014

[J11]

Zhilin Zhang*, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao, “Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG via Block Sparse Bayesian Learning”, IEEE Trans. on Biomedical Engineering, vol.60, no.2, pp.300-309, February 2013 [Most Cited Articles Published in 2013 & 2014 in This Journal, Ranking No.1] 86 Citations Remark: Solved the challenging problem in compressed sensing of less-sparse & non-sparse raw biomedical signals for remote health monitoring; it is the first solid evidence showing that exploiting correlations within signals is an effective way to reconstruct non-sparse signals.

[J10]

Zhilin Zhang*, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao, “Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware”, IEEE Trans. on Biomedical Engineering, vol.60, no.1, pp.221-224, January 2013 (Special Issue on Health Informatics and Personalized Medicine, Acceptance Rate: 23/210 = 10.9%) [Most Cited Articles Published in 2013 & 2014 in This Journal, Ranking No.2] 76 Citations

[J9]

Zhilin Zhang*, Bhaskar D. Rao, “Extension of SBL Algorithms for the Recovery of Block Sparse Signals with Intra-Block Correlation”, IEEE Trans. on Signal Processing, vol.61, no.8, pp.2009-2015, 2013 115 Citations Remark: The first work that studied effects of intra-block correlation in block-sparse models, and proposed the block sparse Bayesian learning framework & algorithms, which have been widely used in many applications.

2012

[J8]

Taiyong Li, Zhilin Zhang*, “Robust Face Recognition via Block Sparse Bayesian Learning”, Mathematical Problems in Engineering, Volume 2013 (2013), Article ID 695976

[J7]

Scott Makeig, Christian Kothe, Tim Mullen, Nima Bigdely-Shamlo, Zhilin Zhang, Kenneth KreutzDelgado, “Evolving Signal Processing for Brain-Computer Interface”, Proceedings of the IEEE, vol. 100, Special Centennial Issue, pp. 1567-1584, May 2012 Invited Paper

2011

[J6]

Zhilin Zhang, Bhaskar D. Rao, “Sparse Signal Recovery with Temporally Correlated Source Vectors Using Sparse Bayesian Learning”, IEEE Journal of Selected Topics in Signal Processing, vol.5, no.5, pp.912-926, 2011 192 Citations Remark: The first work in sparse signal recovery/compressed sensing that exploits statistical correlations in signal amplitudes (i.e., correlations in hidden variables' values); first revealed the importance of exploiting such correlation structures.

2008

2006

[J5]

Zhi-Lin Zhang, “Morphologically Constrained ICA for Extracting Weak Temporally Correlated Signals”, Neurocomputing, vol.71, no.7-9, pp.1669-1679, 2008

[J4]

Yalan Ye, Zhi-Lin Zhang, “A Fast and Adaptive ICA Algorithm with Its Application to Fetal Electrocardiogram Extraction”, Applied Mathematics and Computation, vol.205, no.2, pp.799-806, 2008

[J3]

Zhi-Lin Zhang, Zhang Yi, “Robust Extraction of Specific Signals with Temporal Structure”, Neurocomputing, vol.69, no.7-9, pp.888-893, 2006 72 Citations


[J2]

Zhi-Lin Zhang, Zhang Yi, “Extraction of Temporally Correlated Sources with Its Application to Noninvasive Fetal Electrocardiogram Extraction”, Neurocomputing, vol. 69, no.7-9, pp.900-904, 2006

[J1]

Zhi-Lin Zhang, Zhang Yi, “Extraction of a Source Signal whose Kurtosis Value Lies in a Specific Range”, Neurocomputing, vol.69, no.7-9, pp.894-899, 2006

Conference Publications 2015

[C19]

Zhilin Zhang, Steven Loh, Shadi Abu-Surra, Rakesh Taori, “Mitigation of Phase Noise and Phase Rotation in Single-Carrier Communication Systems Using Pilots and Smoothing Techniques”, IEEE International Conference on Ubiquitous Wireless Broadband, Oct.4-7, 2015

2014

[C18]

Zhilin Zhang, “Heart Rate Monitoring from Wrist-Type Photoplethysmographic (PPG) Signals During Intensive Physical Exercise”, The 2nd IEEE Global Conference on Signal and Information Processing (GlobalSIP 2014), Dec.3-5, 2014

[C17]

Zhilin Zhang, Jae Hyun Son, Ying Li, Mark Trayer, Zhouyue Pi, Dong Yoon Hwang, Joong Ki Moon, “Training-Free Non-Intrusive Load Monitoring of Electric Vehicle Charging with Low Sampling Rate”, The 40th Annual Conference of the IEEE Industrial Electronics Society (IECON 2014), Oct.29-Nov.1, 2014

[C16]

Zhilin Zhang, Bhaskar D. Rao, Tzyy-Ping Jung, “Compressed Sensing for Energy-Efficient Wireless Telemonitoring: Challenges and Opportunities”, Asilomar Conference on Signals, Systems & Computers (Asilomar 2013), California, USA, Nov. 2013

2013

Invited Paper

2012

[C15]

Benyuan Liu, Zhilin Zhang, Hongqi Fan, Qiang Fu, “Compression via Compressive Sensing: A LowPower Framework for the Telemonitoring of Multi-Channel Physiological Signals”, International Workshop on Biomedical and Health Informatics (BHI 2013), Shanghai, China, Dec. 2013

[C14]

D. Labate, F. La Foresta, I. Palamara, G. Morabito, A.Bramanti, Z. Zhang, F.C. Morabito, “EEG Complexity Modifications and Altered Compressibility in Mild Cognitive Impairment and Alzheimer's Disease”, The 23rd Italian Workshop on Neural Networks (WIRN 2013), Salerno, Italy, May 23-25, 2014

[C13]

Jing Wan , Zhilin Zhang , Jingwen Yan, Taiyong Li, Bhaskar D. Rao, Shiaofen Fang, Sungeun Kim, Shannon Risacher, Andrew Saykin, Li Shen, “Sparse Bayesian Multi-Task Learning for Predicting Cognitive Outcomes from Neuroimaging Measures in Alzheimer's Disease”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012), pp.940--947, Jun.16-21, 2012 (# Equal Contribution)

[C12]

Bhaskar D. Rao, Zhilin Zhang, Yuzhe Jin, “Sparse Signal Recovery in the Presence of Intra-Vector and Inter-Vector Correlation”, International Conference on Signal Processing and Communications (SPCOM 2012), India, 2012

#

#

Invited Paper

2011

[C11]

Zhilin Zhang, Bhaskar D. Rao, “Recovery of Block Sparse Signals Using the Framework of Block Sparse Bayesian Learning”, Proc. of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012), Japan, 2012

[C10]

Taiyong Li, Jing Wan, Zhilin Zhang, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Shiaofen Fang, M.Faisal Beg, Lei Wang, “Hippocampus as a Predictor of Cognitive Performance: Comparative Evaluation of Analytical Methods and Morphometric Measures”, MICCAI 2012 Workshop on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders

[C9]

Zhilin Zhang, Bhaskar D. Rao, “Iterative Reweighted Algorithms for Sparse Signal Recovery with Temporally Correlated Source Vectors”, Proc. of the 36th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2011), Czech Republic, May, 2011


[C8]

Zhilin Zhang, Bhaskar D. Rao, “Exploiting Correlation in Sparse Signal Recovery Problems: Multiple Measurement Vectors, Block Sparsity, and Time-Varying Sparsity”, ICML 2011Workshop on Structured Sparsity: Learning and Inference, 2011

2010

[C7]

Zhilin Zhang, Bhaskar D. Rao, “Sparse Signal Recovery in the Presence of Correlated Multiple Measurement Vectors”, Proc. of the 35th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2010), Texas, USA, 2010

2009

[C6]

F. Cong, Z. Zhang, I. Kalyakin, T. Huttunen-Scott, H. Lyytinen, and T. Ristaniemi, “Non-Negative Matrix Factorization vs. FastICA on Mismatch Negativity of Children”, Proc. of 2009 International Joint Conference on Neural Networks (IJCNN 2009), Georgia, USA, 2009

2007

[C5]

Zhi-Lin Zhang, Liqing Zhang, “Linear Prediction Based Blind Source Extraction Algorithms in Practical Applications”, Proc. of the 7th International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2007), Lecture Notes in Computer Science, Vol. 4666, UK, 2007, pp. 309-316

[C4]

Yalan Ye, Jing Wan, Zhi-Lin Zhang, Jia Chen, Lei Wu, “A Flexible Fully-multiplicative Orthogonal-group Based ICA Algorithm”, Proc. of 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2007), Hawaii, 2007

[C3]

Zhi-Lin Zhang, Liqing Zhang, “A Two-Stage Based Approach for Extracting Periodic Signals”, Proc. of the 6th International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2006), LNCS 3889, pp.303-310, South Carolina, USA, 2006

[C2]

Zhi-Lin Zhang, Liqing Zhang, “Two-Stage Temporally Correlated Source Extraction Algorithm with Its Application in Extraction and Classification of Event-Related Potentials”, Proc. of the 13th International Conference on Neural Information Processing (ICONIP 2006), LNCS 4233, pp.523-532, Hong Kong, 2006

[C1]

Xiu-Ling Wu, Liqing Zhang, Zhi-Lin Zhang, “Extraction and Classification of Visual Evoked Potentials Based on a Two-Stage Source Extraction Algorithm”, Proc. of 2006 International Conference on Computational Intelligence and Security (CIS’2006), Nov.2006

2006

Journal Publications in Chinese 2013

[CJ2]

Taiyong Li, Huijun Wang, Jiang Wu, Zhilin Zhang, Changjie Tang, “Sparse Bayesian Learning for Credit Risk Evaluation”, Journal of Computer Applications (Chinese Journal), vol. 33, no. 11, pp. 3094 - 3096, 2013

2012

[CJ1]

Hong Sun, Zhilin Zhang, Lei Yu, “From Sparsity to Structured Sparsity: Bayesian Perspective”, Signal Processing (Chinese Journal), vol. 28, no. 6, pp. 759-773, 2012 Invited Paper

DISSERTATION AND THESIS 2012

[T2]

Zhilin Zhang, “Sparse Signal Recovery Exploiting Spatiotemporal Correlation”, University of California, San Diego, Ph.D. Dissertation

2005

[T1]

Zhilin Zhang, “Independent Component Analysis with Applications to Biomedical Signal Processing”, University of Electronic Science and Technology of China, Master Thesis

HONORS AND AWARDS 2015

Most Cited Articles Published in Recent Years in IEEE Trans. on Biomedical Engineering For the paper "TROIKA: A General Framework for Heart Rate Monitoring Using Wrist-Type


Photoplethysmographic Signals During Intensive Physical Exercise " http://tbme.embs.org/research-highlights/most-cited-articles/ 2014

Most Cited Articles Published in 2013 & 2014 in IEEE Trans. on Biomedical Engineering (ranking No.1) For the paper "Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG via Block Sparse Bayesian Learning" http://tbme.embs.org/research-highlights/most-cited-articles/

2014

Most Cited Articles Published in 2013 & 2014 in IEEE Trans. on Biomedical Engineering (ranking No.2) For the paper "Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware " http://tbme.embs.org/research-highlights/most-cited-articles/

2015

Samsung Prolific Author Award

2015

Samsung Achievement Award For contributions to phase noise mitigation in wireless communication systems

2014

Samsung Achievement Award For contributions to smart-home and wearable health monitoring

2014

Samsung Outstanding Individual Employee of the Year Award

2013

Samsung Achievement Award For contributions to biosensing and biomedical signal processing

2012

CVPR Doctoral Consortium Scholarship

2007 -- 2012

Research Assistant Scholarship University of California, San Diego

2005 -- 2007

Innovation Funding for Graduate Student Research University of Electronic Science and Technology of China Awarded to no more than 1 student per year among 2000+ graduate students based on research ability and research leadership; 30000 RMB/year)

2005 -- 2007

National Academic Visiting Fellowship for Graduate Students, China

2006

ICONIP'06 Travel Grant

2005

Outstanding Master Thesis Award University of Electronic Science and Technology of China

2005

The Second Prize in College Student Entrepreneur Competition For a prototype of fetal ECG monitor, University of Electronic Science and Technology of China

2004 -- 2005

First Grade Scholarship Top 1%, University of Electronic Science and Technology of China

2003

Special Grade Scholarship Top 0.1%, University of Electronic Science and Technology of China


INVITED TALKS August 2013

September 2012

August 2012

“Sparse Signal Recovery Exploiting Spatio-Temporal Correlation” University of Electronic Science and Technology of China, Sichuan, P.R.China “Block Sparse Bayesian Learning with Applications to Wireless Telemonitoring of Physiological Signals” Qualcomm Inc., CA, USA “Sparse Linear Regression by Sparse Bayesian Learning” Experian Inc., CA, USA

July 2012

“Block Sparse Bayesian Learning with Applications to Wireless Telemonitoring of Physiological Signals” University of California, San Diego, CA, USA

July 2012

“Sparse Signal Recovery by Sparse Bayesian Learning: Models, Algorithms, and Applications” Samsung Research America, TX, USA

August 2011

“Sparse Bayesian Learning: Models, Algorithms, and Applications” Indiana University, IN, USA

March 2011

“Sparse Signal Recovery with Temporally Correlated Source Vectors Using Sparse Bayesian Learning” University of California, San Diego, CA, USA

LEADERSHIP 2014 - current

2005 - 2007

Director of Advanced Signal Processing and Intelligent Systems Laboratory An international research group consisting of 10 researchers with PhD degree. Leader of Blind Source Separation Research Group of University of Electronic Science and Technology of China A university-wise research group consisting of 6 graduate students, with research funding of 60000 RMB from UESTC.

PROFESSIONAL ACTIVITIES AND INTERNATIONAL RECOGNITION Technical Committees

Member of the Bio-Imaging and Signal Processing Technical Committee of the IEEE Signal Processing Society (Jan 1st, 2014 -- Dec.31st, 2016)

Organizer

2015 IEEE Signal Processing Cup: “Heart Rate Monitoring During Physical Exercise Using WristType Photoplethysmographic (PPG) Signals”

Editorship

Associate Editor for IEEE Journal of Translational Engineering in Health and Medicine (since 2014)

Technical Program Committees

2014 IEEE International Conference on Image Processing (ICIP 2014) 2014 IEEE International Conference on Multimedia & Expo (ICME 2014) 2014 International Conference on Big Data Science and Computing (BigDataScience 2014) 2014 Int. Conference on Digital Image Computing: Techniques and Applications (DICTA 2014) 2015 International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing (CoSeRa 2015) 2015 IEEE International Conference on Multimedia & Expo (ICME 2015) 2015 IEEE International Conference on Image Processing (ICIP 2015)


Membership

since 2015 2013 -- 2014

Journal Reviewer

Conference Reviewer

Senior Member of IEEE Senior Member of IEEE Signal Processing Society Senior Member of IEEE Engineering in Medicine and Biology Society Member of IEEE Member of IEEE Signal Processing Society Member of IEEE Engineering in Medicine and Biology Society

since 2015 since 2012 since 2007 since 2012 since 2012 since 2014 since 2015 since 2014 since 2012 since 2012 since 2011 since 2014 since 2015 since 2013 since 2013 since 2013 since 2013 since 2012 since 2013 since 2013 since 2013 since 2011 since 2013 since 2008 since 2012

IEEE Internet of Things Journal IEEE Journal of Biomedical and Health Informatics IEEE Signal Processing Letters IEEE Trans. on Biomedical Circuits and Systems IEEE Trans. on Biomedical Engineering IEEE Trans. on Circuits and Systems II IEEE Trans. on Human-Machine Systems IEEE Trans. on Industrial Electronics IEEE Trans. on Image Processing IEEE Trans. on Neural Networks and Learning Systems IEEE Trans. on Signal Processing IET Signal Processing BioMedical Engineering Online Biomedical Signal Processing and Control Circuits, Systems & Signal Processing Computers and Electrical Engineering Computers in Biology and Medicine Digital Signal Processing International Journal of Neural Systems Medical & Biological Engineering & Computing Neural Computing and Applications Neurocomputing PLOS One Signal Processing The European Physical Journal

2013 - 2016 2014 - 2016 2014 - 2016 2013 2013 - 2016 2013 2013

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) IEEE International Conference on Image Processing (ICIP) IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI) IEEE International Symposium on Information Theory (ISIT) IEEE International Conference on Multimedia and Expo (ICME) IEEE International Workshop on Multimedia Signal Processing (MMSP) IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) International Conference on Sampling Theory and Applications (SampTA)

2013
