School of Engineering

Staff Profile

Professor Jonathon Chambers

Professor of Signal and Information Processing

Background

Jonathon Chambers is a widely-experienced academic and research leader and an expert in adaptive signal processing and machine learning and their application in biomedicine, communications and defence.  He holds PhD (1990) and DSc (2014) degrees from Imperial College. He joined the School of Electrical and Electronic Engineering at Newcastle University in 2015 which, from 1st August 2017, became part of the School of Engineering.  He is the Head of the Intelligent Sensing and Communications (ISC) Group. 

He is an International Honorary Dean and Guest Professor within the College of Automation, Harbin Engineering University supported by the Chinese Govt's 1000 Talents Programme and previously by the High-End Expert Programme.

He has secured more than 30 research projects from industry and government to the value of more than £12M.  He is the Director of one of the two Dstl/EPSRC University Defence Research Collaboration consortia, LSSCN, which is running between 2013 and 2018, and led from Newcastle University.  He has co-authored two research monographs, one in non linear adaptive signal processing and a second in EEG signal processing, both appearing with Wiley, in 2001 and 2007, respectively; and has published more than 500 other scientific works, including more than 180 journal papers, and has steered 78 researchers to PhD graduation.

Jonathon holds Visiting Professor positions at King's College London and Loughborough University and has additionally held senior academic positions at Cardiff University and Imperial College.  He has served as an Associate Editor/Senior Area Editor for IEEE journals, including IEEE Trans. Signal Processing, for more than ten years and was a Co-Technical Programme Chair  for the IEEE flagship conference in Signal Processing, ICASSP, held in Prague, 2011.  He is currently an Area Editor in Communications Signal Processing for Digital Signal Processing and an Associate Editor for Advances in Signal Processing.  He is additionally a member of the organising committee of ICASSP 2019 and 2022 which will be held in Brighton, UK and Singapore.  He is also a co-academic chair for FUSION 2018 which will be held at the University of Cambridge, UK. 

He was awarded the first QinetiQ Visiting Fellowship in 2007 "for his outstanding contributions to adaptive signal processing and his contributions to QinetiQ" as a result of his successful collaboration with the signal processing team at Malvern.  He also received the Teaching Excellence Award from the Department of Electronic and Electrical Engineering at Loughborough University and he was awarded one of the four Research-Informed Teaching Awards from Loughborough University in 2013.

He was elected as a Fellow of the Royal Academy of Engineering in 2012 and was elevated to a Fellow of the IEEE in 2011.  He is also a Fellow of the IET and Institute of Mathematics and its Applications (IMA).

Current major research interests: advanced signal processing for wireless communication systems and multimodal technologies (audio-visual) to support human interaction; together with signal processing for assisted living and signal processing for the networked battlespace.

Research

Jonathon is a member of the Intelligent Sensing and Communications Group his publication profile can be viewed at Google Scholar and his background as a researcher at ORCID Profile

Current Major Research Interests and Active Research Projects

Adaptive signal processing, estimation theory, robust statistics and machine learning

Applications: assisted living; defence; human machine interaction and wireless communications 

(PI) 2013-2018 EP/K014307/1,2 "Signal Processing Solutions for the Networked Battlespace", Dstl/EPSRC, £4.3M [FEC], collaboration with Loughborough, Surrey, Strathclyde and Cardiff.

(CI) 2015-2018 EP/M015475/01 "Massive MIMO Wireless Networks: Theory and Methods", EPSRC, £1M [FEC], collaboration with Loughborough, KCL and UCL. 

(PI) 2016-2019 "Multimodal Wide Area Surveillance", Thales & EPSRC, ICASE Award, £52K.

(CI) 2017-2020 EP/R002665/1 "Full Duplex for Underwater Acoustic Communications", EPSRC, £517K (FEC), collaboration with York and Atlas Elektronik UK

(PI) 2017-2020 EP/R006377/1 "Communications Signal Processing Solutions for Massive Machine-to-Machine Commmunications", EPSRC, £340K (FEC), collaboration with KCL, QMUL and Lboro 

Selected PhD Graduates (Total 78):

2017 M. Abdullah, Advancing Iris Biometric Technology

2017 W. Rafique, Enhanced Independent Vector Analysis for Speech Separation in Room Environments

2016 Z. Zohny, Robust Variational Bayesian Clustering for Underdetermined Speech Separation

2016 P. Feng, Enhanced Particle PHD Filtering for Human Tracking 

2016 J. Harris, Online Source Separation in Reverberant Environments Exploiting Known Source Locations

2015 Z. Tian, Buffer-Assisted Relay Networks

2015 W. Qaja, Distributed Space Time Block Coding and Application in Cooperative Cognitive Relay Networks

2015 P. Wheeler, Adaptive Notch Filtering for Multiple Complex Sinusoidal Signals

2015 L. Ge, Distributed Space-Time Coding including the Golden Code with Application in Cooperative Wireless Networks

2015 M. Manna, Modified Quasi-Orthogonal Space-Time Block Coding in Distributed Wireless Networks

2014 M. Eddaghel, Mitigating PAPR in Cooperative Wireless Networks with Frequency Selective Channels and Relay Selection

2014 A. Rhuma, Intelligent Computer Vision Processing Techniques for Fall Detection in Enclosed Environments

2014 U. Mannai, Novel Transmission Schemes for Application in Two-way Cooperative Relay Wireless Communication Networks

2014 O. Alnatouch, Distributed Transmission Schemes for Wireless Communication Networks

2014 A. ur-Rehman, Bayesian-Based Techniques for Tracking Multiple Humans in an Enclosed Environment

2013 Y. Liang, Enhanced Independent Vector Analysis for Audio Separation in a Room Enviroment

2013 M.S. Khan, Informed Algorithms for Sound Source Separation in Enclosed Reverberant Environments

2013 M. Yu, Computer Vision Based Techniques for Fall Detection with Application Towards Assisted Living
 
2012 A. Elazreg, Distributed Space-Time Block Coding in Asynchronous Cooperative Relay Networks
 
2012 G. Chen, Rate Enhancement and Multi-Relay Selection Schemes for Application in Wireless Cooperative Networks
 
2012 F. Alotaibi, Distributed Space-Time Block Coding in Cooperative  Relay Networks with Application in Cognitive Radio

2012 M. Hayes, Distributed Quasi-Orthogonal Space-Time Coding in Wireless Cooperative Relay Networks

2011 A. Anandkumar, Robust Game-Theoretic Algorithms for Distributed Resource Allocation in Wireless Communications

2009 L. Li, Adaptive Algorithms and Variable Structures for Distributed Estimation

2009 S.M. Naqvi, Multimodal Methods for Blind Source Separation of Audio Sources

2009 N.E. Eltayeb , Space-Time Coding for Broadband Point-to-Point and Cooperative Wireless Communications

2008 T. Tsalaile, Digital Signal Processing Algorithms and Techniques for the Enhancement of Lung Sound Measurement

2008 A. Aubrey, Exploiting the Bi-modality of Speech in the Cocktail Party Problem

2008 J. Foster, Algorithms and Techniques for Polynomial Matrix Decompositions

2007 Y. Zhang Adaptive Algorithms and Structures with Potential Application in Reverberation Time Estimation in Occupied Rooms

2007 C.C. Took, Blind Source Separation via Independent and Sparse Component Analysis with Application to Temporomandibular Disorder

2006 R. Nawaz, Low Complexity Channel Shortening and Equalization for Multicarrier Systems

2006 T. Bowles, Signal Processing Techniques for the Interpretation of Microarray Measurements

2005 Z. Zhang, Sinusoidal Frequency Estimation with Applications to Ultrasound

2003 M. Klajman, Mixed Statistics in Blind Source Separation

2002 P. Yuvapoositanon, Blind Adaptive Techniques for Direct-Sequence Code Division Multiple Access Receivers

2002 Y. Luo, A Mixed Cross-Correlation and Constant Modulus Adaptive Algorithm for Joint Blind Equalization and Source Separation

2002 M. Jafari, Novel Sequential Algorithms for Blind Source Separation of Instantaneous Mixtures

2001 N. Forsyth, A Subband and Noise Robust Approach to Stereophonic Echo Cancellation

2001 N. Tangsangiumvisai, Algorithms and Structures for Stereophonic Acoustic Echo Cancellation

2001 C. Topping, Moving Object Enhancement in Noisy Video Sequences

1999 D. Mandic, Recurrent Neural Networks for Prediction: Architectures and Stability

1998 D. Brookes, Adaptive Algorithms for Low Complexity Equalizers in Mobile Communications

1997 S. Lambotharan, Algorithms and Structures for Blind Channel Equalization

1996 N. Chotikakamthorn, A Pre-Filtering Maximum Likelihood Approach to Multiple Source Direction Estimation

 

Teaching

 

Jonathon is involved in the modules EEE3004 (Digital Signal Processing) and EEE8001 (Estimation).

EEE3004 Objectives: -

At the end of this unit students should

(i) understand the implications of the sampling theorem and the consequences of aliasing and quantisation distortion

(ii) appreciate the importance of the z-transform and its properties; and the impulse response and transfer function of a digital filter 

(iii) have an awareness of different structures available for the realisation of finite impulse impulse response (FIR) and infinite impulse response (IIR) digital filters

(iv) be familiar with ideal filter approximation functions

(v) be able to design certain linear phase FIR and IIR filters to meet prescribed specifications

(vi) be able to use the discrete Fourier transform (DFT) and its fast form (FFT) to perform signal analysis and be conscious of spectral leakage and smearing effects

(vii) have an appreciation of the building blocks of digital multirate signal processing, decimators and interpolators, and their practical application in filter realization, sample-rate conversion and speech coding.

EEE8001 Objectives:-

At the end of this unit students should

(i) be able to explain the concepts of ensemble average, statistical stationarity, wide-sense stationarity and ergodicity

(ii) be able to interpret autocorrelation and cross-correlation functions and utilize these to explain the operation of linear systems excited by wide-sense stationary random signls

(iii) be able to state the Wiener-Khinchine theorem and use auto and cross power spectral densities in typical instrumentation applications

(iv) understand the concepts of estimate and estimator

(v) appreciate the roles of bias and variance in measuring the performance of an estimator

(vi) be able to derive the MVUE on the basis of of Cramer Rao Lower Bound theory

(vii) be able to utilise the BLUE and Maximum Likelihood estimators

(viii) understand the notion of a sequential estimator and apply adaptive signal processing based on MMSE and the Kalman filter in tracking.

Publications