Constantinides Workshop

 

Constantinides Workshop íV Session I

Time: August 22, 14:00 íV 15:45
Place: Room Y301
Chair: Prof W.C. Siu, The Hong Kong Polytechnic University (Hong Kong)
Title: Low Complexity Lattice Filter for Finite Word-length Implementation
Speaker: Professor Yong Ching Lim, Nanyang Technological University
(Singapore)

Title: Iterative Regularization for the Inverse Problems in Speech and Image Processing
Speaker: Dr Daniel P.K. Lun, The Hong Kong Polytechnic University
(Hong Kong)

Constantinides Workshop íV Session II

Time: August 22, 16:15 íV 18:00
Place: Room Y301
Chair: Prof H.K. Kwan, University of Windsor (Canada)
Title: Signal Processing for Next Generation Wearable Health: Challenges and Solutions
Speaker: Professor Danilo Mandic, Imperial College London
(UK)

Title: Use of Signal Processing Techniques in Bioinformatics
Speaker: Dr Bonnie N.F. Law, The Hong Kong Polytechnic University
(Hong Kong)

Constantinides Workshop íV Session III

Time: August 23, 8:30 íV 10:15
Place: Room Y301
Chair: Prof Yong Ching Lim, Nanyang Technological University (Singapore)
Title: Iris Texture Analysis for Human Identification
Speaker: Professor Tieniu TAN, Chinese Academy of Sciences
(China)

Title:Kernel Memory -- A New Connectionist Framework and Its Application to Spoken Word Recognition and Modelling Cognitive Faculties
Speaker: Professor Tetsuya Hoya, Nihon University (Japan)

Title: Audiovisual Speech Source Separation
Speaker: Professor Jonathon A. Chambers, Loughborough University
(UK)

Constantinides Workshop íV Session IV

Time: August 23, 10:45 íV 12:00
Place: Room Y301
Chair: Prof Tieniu Tan, Chinese Academy of Sciences (China)
Title: Mocap Signal Processing: Data Recovery, Compression and Application
Speaker: Dr Chau Lap-Pui, Nanyang Technological University (Singapore)

Title: Recent Advances in Sparse FIR Filter Design using l0/l1 Optimization Techniques
Speakers:Aimin Jiang, Hohai University (China)
H. K. Kwan, University of Windsor (Canada)

Forum: Information and Direction of Future DSP Conferences

Time: August 23, 12:00 - 12:30
Place: Room Y301
Chair: Prof. Tieniu Tan, Chinese Academy of Sciences (China)
Introduction: Prof. W.C. Siu, The Hong Kong Polytechnic University (Hong Kong)

Forum attendees: A.G. Constantinides, f. harris, Kin K Leung, Yong Ching Lim, Daniel P.K. Lun, Danilo Mandic, H.K. Kwan, Yui-Lam Chan, Bonnie N.F. Law, Shing Chow Chan, Hing Cheung So, Chris Y.H. Chan, Tan Lee, Lap-Pui Chau, Frank Leung, Edward Cheung, Y.W. Liu.
All are welcome.


Constantinides Workshop íV Session I

Time: August 22, 14:00 íV 15:45
Place: Room Y301
Chair: Prof W.C. Siu, The Hong Kong Polytechnic University (Hong Kong)

 
Professor Yong Ching Lim, PhD, DIC, FIEEE (invited speaker)
Nanyang Technological University (Singapore)

Speech Title: Low Complexity Lattice Filter for Finite Word-length Implementation

Abstract:
Coefficient word-length and signal word-length are two of the yardsticks determining the complexity of a digital filter. Coefficient word-length reduction causes frequency response deterioration and signal word-length reduction causes round off performance deterioration. Several methods for minimizing performance deterioration due to coefficient word-length reduction and signal word-length reduction for a digital lattice filter will be presented.

LIM Yong Ching received the A.C.G.I. and B.Sc. degrees in 1977 and the D.I.C. and Ph.D. degrees in 1980, all in electrical engineering, from Imperial College, London, U.K. Since 2003, he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, where he is currently a professor. From 1980 to 1982, he was a National Research Council Research Associate in the Naval Postgraduate School, Monterey, California. From 1982 to 2003, he was with the Department of Electrical Engineering, National University of Singapore. His research interests include digital signal processing and VLSI circuits and systems design. Dr. Lim was a recipient of the 1996 IEEE Circuits and Systems Society's Guillemin-Cauer Best Paper Award, the 1990 IREE (Australia) Norman Hayes Memorial Best Paper Award, 1977 IEE (UK) Prize and the 1974-77 Siemens Memorial (Imperial College) Award. He served as a lecturer for the IEEE Circuits and Systems Society under the distinguished lecturer program from 2001 to 2002 and as an associate editor for the IEEE Transactions on Circuits and Systems from 1991 to 1993 and from 1999 to 2001. He has also served as an associate editor for Circuits, Systems and Signal Processing from 1993 to 2000. He served as the Chairman of the DSP Technical Committee of the IEEE Circuits and Systems Society from 1998 to 2000. He served in the Technical Program Committee's DSP Track as the Chairman in IEEE ISCAS'97 and IEEE ISCAS'00 and as a Co-chairman in IEEE ISCAS'99. He was the General Chairman for IEEE APCCAS 2006, a Co-General Chairman for IEEE ISCAS 2009, ICGCS 2010, and DSP 2014.

 
Dr Daniel P.K. Lun, PhD, CEng, MIET, MHKIE, SrMIEEE (invited speaker)
The Hong Kong Polytechnic University (Hong Kong)

Speech Title: Iterative Regularization for the Inverse Problems in Speech and Image
Processing

Abstract:
Inverse problems abound in many application areas of speech and image processing. In such problems, the goal is to estimate an unknown original signal/image from an observation which is possibly distorted due to the different imperfections of the working environment. However, the generalized inverse operators can be unbounded or have a very large norm. Regularization is often needed to make the estimation process numerically stable and converge to the optimal result. Recently, there has been an increasing interest in the L1 norm regularization methods. They have the beneficial effects of regularizing model coefficients and yield sparse models that are more easily interpreted. They have been generally applied in many inverse problems in which the number of parameters to be estimated is sparse as compared to the observations. In this talk, the applications of iterative regularization to a few digital signal processing problems, namely, compressive sensing of images, speech enhancement and 3D object model reconstruction, are discussed.

Daniel, P.K. Lun received his BSc (Hons) degree with first-class honours from the University of Essex, U.K., and Ph.D degree from the Hong Kong Polytechnic University (formerly called Hong Kong Polytechnic) in 1988 and 1991, respectively. In 1992, he joined the Hong Kong Polytechnic University as a lecturer. He is now the Associate Head of the Department of Electronic and Information Engineering of the Hong Kong Polytechnic University. Dr Lun is active in research activities. He has published more than 120 international journals and conference papers. One of his research projects "A study of the Computer Tomography and the Wavelet Transform" was rated as Excellent by the Hong Kong Research Grants Council. His research students have also received two best paper awards in international conferences. He was the Chairman of the IEEE Hong Kong Chapter of Signal Processing in 1999-00. He was the General Chair of 2014 International Conference on Digital Signal Processing (DSP 2014), 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing (ISIMP2004), and the Technical Co-Chair of 2015 Asia-Pacific Signal and Information Processing Association (APSIPA) Conference. He was also the Finance Chair of 2003 IEEE International Conference on Acoustics, Speech and Signal Processing, as well as 2010 IEEE International Conference on Image Processing (ICIP2010). Both of them are the flagship conferences of the IEEE Signal Processing Society. He received the Certificate of Merit from the IEEE Signal Processing Society for dedication and leadership in organizing the 2010 IEEE International Conference on Image Processing (ICIP). He was the Editor of HKIE Transactions published by the Hong Kong Institution of Engineers (HKIE). He was also the leading guest editor of a special issue of EURASIP journal of Advances in Signal Processing. He is a member of the IEEE Circuits and Systems Society Digital Signal Processing as well as Visual Signal Processing and Communications Technical Committees. He is a Chartered Engineer, a corporate member of IET, HKIE and a senior member of IEEE.

Constantinides Workshop íV Session II

Time: August 22, 16:15 íV 18:00
Place: Room Y301
Chair: Prof H.K. Kwan, University of Windsor (Canada)

 


Professor Danilo Mandic, PhD, DIC, FIEEE (invited speaker)
Imperial College London (UK)

Speech Title: Signal Processing for Next Generation Wearable Health: Challenges and Solutions

Abstract: An insight into the processing of vector sensor data is provided from a Signal Processing perspective. By processing such data in the vector spaces where they naturally reside (2D, 3D, 4D), we show how the notion of noncircularity of probability distributions can be used to enhance the number of degrees of freedom in the processing. This helps to remove ambiguity and uncertainty in modelling, thus enabling identification and separation even when there is more than one Gaussian source present. Next, a brief account of multiscale processing of such data will be given from a time-frequency perspective, in order to bypass the mathematical artefacts associated with the Fourier and wavelet approaches. Finally, a complexity science perspective of vector sensor data processing will be illuminated, with application in human centred signal processing (stress, fatigue, pathology).

Danilo Mandic received the Ph.D. degree in nonlinear adaptive signal processing in 1999 from Imperial College, London, London, U.K. He is now a Reader with the Department of Electrical and Electronic Engineering, Imperial College London, London, U.K. He has previously taught at the Universities of East Anglia, Norwich, Norfolk, U.K., and Banja Luka, Bosnia Herzegovina. He has written over 150 publications on a variety of aspects of signal processing and a research monograph on recurrent neural networks. He has been a Guest Professor at the Catholic University Leuven, Leuven, Belgium and Tokyo University of Agriculture and Technology (TUAT), and Frontier Researcher at the Brain Science Institute RIKEN, Tokyo, Japan. Dr. Mandic has been a Member of the IEEE Signal Processing Society Technical Committee on Machine Learning for Signal Processing, Associate Editor for IEEE Transactions on Circuits and Systems II, and Associate Editor for International Journal of Mathematical Modeling and Algorithms. He has won awards for his papers and for the products coming from his collaboration with industry.

 


Dr Bonnie N.F. Law, PhD, SrMIEEE (invited speaker)
The Hong Kong Polytechnic University (Hong Kong)

Speech Title: Use of Signal Processing Techniques in Bioinformatics

Abstract:
With the advancement in DNA sequencing technologies and high-throughput technologies, it is now feasible for sequencing individual genomes and measuring expression profiles of thousands of genes simultaneously. The analysis of such a large amount of data thus requires efficient and effective computational methods. Signal processing techniques have been utilized in various applications. They are able to model the signals in another domain and extract interesting features embedded in the signal. In this talk, we will apply signal processing techniques for gene expression data analysis and DNA sequence compression. In gene expression data analysis, signal processing techniques will be applied to identify co-expressed genes (biclusters) which likely possess similar biological functions. We consider biclusters as some kinds of patterns in which the bicluster detection problem then becomes a pattern recognition problem. In DNA sequence compression, we will discuss the similarity among a set of DNA sequences so that the inter-sequence similarity can be used to compress them to reduce storage space.

Bonnie N.F. Law received the BEng (Hons) degree with first-class honours from the University of Auckland, New Zealand in 1993 and a PhD degree from the University of Tasmania, Australia in 1997. She is currently an associate professor in the Department of Electronic and Information Engineering, the Hong Kong Polytechnic University. Her research interests include signal processing, wavelet transform, image enhancement, compression and forensics. Recently she has also extended her study into a new area on bioinformatics, working on gene expression and DNA sequence analysis. Novel results for gene expression data analysis and efficient biclustering algorithms have been achieved and published in international journals with good attention from peers, such as a paper in 2008 has been classified as a 'highly access' article in BMC Bioinformatics journal.

Constantinides Workshop íV Session III

Time: August 23, 8:30 íV 10:15
Place: Room Y301
Chair: Prof Yong Ching Lim, Nanyang Technological University (Singapore)

 


Professor Tieniu TAN, PhD, DIC, FIEEE (invited speaker)
Chinese Academy of Sciences (China)

Speech Title: Iris Texture Analysis for Human Identification

Abstract:
Texture is an important image property which has been exploited in a wide variety of visual tasks. The rich and unique texture present in the iris regions of human eyes makes iris recognition a very reliable way of identifying individuals. In this talk, we will discuss how the rich texture in the human iris can be characterized and exploited for reliable human identification. For completeness, we will also touch on other modules of a typical iris recognition system such as iris region segmentation and iris pattern matching. A number of important practical applications will also be presented.

Tieniu Tan received his B.Sc. degree in electronic engineering from Xi'an Jiaotong University, China, in 1984, and his MSc and PhD degrees in electronic engineering from Imperial College London, U.K., in 1986 and 1989, respectively. In October 1989, he joined the Computational Vision Group at the Department of Computer Science, The University of Reading, U.K., where he worked as a Research Fellow, Senior Research Fellow and Lecturer. In January 1998, he returned to China to join the National Laboratory of Pattern Recognition (NLPR), Institute of Automation of the Chinese Academy of Sciences (CAS) as a full professor. He was the Director General of the CAS Institute of Automation from 2000-2007, and the Director of the NLPR from 1998-2013. He is currently Director of the Center for Research on Intelligent Perception and Computing at the Institute of Automation and also serves as Deputy Secretary-General of the CAS and the Director General of the CAS Bureau of International Cooperation. He has published more than 400 research papers in refereed international journals and conferences in the areas of image processing, computer vision and pattern recognition, and has authored or edited 11 books. He holds more than 70 patents. His current research interests include biometrics, image and video understanding, and information forensics and security.

Dr Tan is a Member of the Chinese Academy of Sciences, and a Fellow of the IEEE and the IAPR (the International Association of Pattern Recognition). He currently serves as President of the IEEE Biometrics Council, First Vice President of the IAPR and Deputy President of the Chinese Association for Artificial Intelligence. He was the Founding Chair of the IAPR Technical Committee on Biometrics, the IAPR/IEEE International Conference on Biometrics (ICB), the IEEE International Workshop on Visual Surveillance, Asian Conference on Pattern Recognition (ACPR) and Chinese Conference on Pattern Recognition (CCPR). He was the Executive Vice President of the Chinese Society of Image and Graphics, Deputy President of the China Computer Federation and the Chinese Automation Association. He has served as chair or program committee member for many major national and international conferences. He is or has served as Associate Editor or member of editorial boards of many leading international journals including IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Circuits and Systems for Video Technology, Pattern Recognition, Pattern Recognition Letters, Image and Vision Computing, etc. He is Editor-in-Chief of the International Journal of Automation and Computing. He has given invited talks and keynotes at many universities and international conferences, and has received numerous national and international awards and recognitions.

 


Professor Tetsuya Hoya, PhD, DIC, SrMIEEE (invited speaker)
Nihon University (Japan)

Speech Title: Kernel Memory -- A New Connectionist Framework and Its Application to Spoken Word Recognition and Modelling Cognitive Faculties

Abstract:
The concept of kernel memory was presented as a novel connectionist paradigm in the monograph (Hoya, 2005). Within the concept, each node in the network can hold a different type of activation function, which allows us to process simultaneously multiple domain data by a single, composite model. On the other hand, the notion of lateral connections established via the 'link weights' essentially removes topological constraints of a network. Normally, a network of kernel memory is constructed via a simple, self-structuring learning process, given a set of training data, which does not resort to a conventional delta-rule type network training algorithm. In the talk, I will first give a summary of the kernel memory and then focus upon its application to performing spoken word recognition tasks and modelling cognitive faculties, on the basis of the previous works.

Tetsuya Hoya was born in Tokyo, Japan, in Sept. 1969. He received the B.Sc. and M.Sc. degrees in electrical engineering from Meiji University in 1992 and 1994, respectively. In 1994, he became a Ph.D. student at Imperial College, under the supervision of Prof. A. G. Constantinides, and received a Ph.D./DIC degree from Imperial College/University of London in 1998. He worked as a Postdoctoral Research Associate at Imperial College, from Sept. 1997 to Aug. 2000. From Oct. 2000 to Mar. 2006, he was a Research Scientist at the BSI-RIKEN. Since Apr. 2007, he has been an Associate Professor at the Department of Mathematics, College of Science and Technology, Nihon University. He has published more than 40 technical papers and is the single author of the monograph Artificial Mind System -- Kernel Memory Approach, which began the new series: Studies in Computational Intelligence (SCI) (Springer-Verlag: 2005). His research interest lies in a wide spectrum of computational intelligence: artificial intelligence, cognitive neuroscience, combinatoric optimization, computational linguistics, consciousness studies, neural networks, philosophy, psychology, robotics, and signal processing. Dr. Hoya was a committee member of the Fourth International Symposium on Independent Component Analysis and Blind Signal Separation (ICA-2003). From Apr. 2007 to May 2011, he has served as an Associate Editor for IEICE Trans. on Fundamentals. He is the corecipient of the Best Paper Award at the IEEE International Conference on Very Large Scale Integration Design and Video Technology, Shanghai, in 2005.

 

Professor Jonathon A. Chambers, PhD, DSc, DIC, FREng, C.Eng, FIET, FIEEE, FHEA (invited speaker)
Loughborough University (UK)

Speech Title: Audiovisual Speech Source Separation

Abstract:
The separation of speech signals observed at multiple microphones in noisy and reverberant environments using only the audio modality has limitations because there is generally too little information to discriminate fully the different sound sources. Humans overcome this problem by exploiting the visual modality, which is insensitive to background noise and can provide contextual information describing the audio scene. This advantage has inspired the creation of the new field of audiovisual (AV) speech source separation that aims at exploiting visual modality alongside the microphone measurements in a machine.

Progress in this emerging field will expand the application of voice-based machine interfaces, such as Siri, the intelligent personal assistant on the iPhone and iPad, to much more realistic settings and thereby provide more natural human-machine interfaces. Further details can be found in "Audiovisual Speech Source Separation: An overview of key methodolgies", IEEE Signal Processing Magazine, Vol. 31, No. 3, pp. 125-134, May 2014.

Jonathon A. Chambers (j.a.chambers@lboro.ac.uk) received his PhD degree from Imperial College, London, United Kingdom, in 1990, and he had the very good fortune to have Professor Tony Constantinides as his advisor. He is Professor of Communications and Signal Processing and currently leads the Advanced Signal Processing within the School of Electronic, Electrical, and Systems Engineering at Loughborough University. From 1st October 2014 he will become the Head of the Department of Electronic Engineering at the University of Surrey, UK. He is a Senior Area Editor for the IEEE Transactions on Signal Processing and a member of the IEEE SIgnal Processing Society Conference Board, having previously served on the IEEE Signal Processing Society Technical Committee on Signal Processing Theory and Methods and the Awards Board. He is a Fellow of the IEEE and the Royal Academy of Engineering, United Kingdom.

Constantinides Workshop íV Session IV

Time: August 23, 10:45 íV 12:00
Place: Room Y301
Chair: Prof Tieniu Tan, Chinese Academy of Sciences (China)

 


Dr Chau Lap-Pui, PhD, SrMIEEE (invited speaker)
Nanyang Technological University (Singapore)

Speech Title: Mocap Signal Processing: Data Recovery, Compression and Application

Abstract:
Motion capture (mocap) is the process of recording the motion of human. In film production and video game industries, it refers to recording motion of human actors, and using that information to animate character models in 2D or 3D animation. As number of sensors increase, large number of data need to be stored and transmitted. Reducing data size by compression is always an important topic. Besides, the depth map camera which can be used to generate mocap data becomes more and more popular nowaday, it reduces the cost to develop new mocap application. This talk will (i) simply introduce motion capture, (ii) data recovery due to transmission and occulsion problem, (iii) compression techniques to reduce the data size, and (iv) application on fall detection.


Lap-Pui Chau received the B. Eng degree with first class honours in Electronic Engineering from Oxford Brookes University, England, and the Ph.D. degree in Electronic Engineering from Hong Kong Polytechnic University, Hong Kong, in 1992 and 1997, respectively. In June 1996, he joined Tritech Microelectronics as a senior engineer. Since March 1997, he joined Centre for Signal Processing, a national research centre in Nanyang Technological University as a research fellow, subsequently he joined School of Electrical & Electronic Engineering, Nanyang Technological University as an assistant professor and currently, he is an associate professor. His research interests include fast signal processing algorithms, scalable video and video transcoding , robust video transmission, image representation for 3D content delivery, and human motion analysis.

He involved in organization committee of international conferences including the IEEE International Conference on Image Processing (ICIP 2010, ICIP 2004), and IEEE International Conference on Multimedia & Expo (ICME 2010). He is a Technical Program Co-Chairs for Visual Communications and Image Processing (VCIP 2013) and 2010 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS 2010). He was the chair of Technical Committee on Circuits & Systems for Communications (TC-CASC) of IEEE Circuits and Systems Society from 2010 to 2012, and the chairman of IEEE Singapore Circuits and Systems Chapter from 2009 to 2010. He served as an associate editor for IEEE Transactions on Multimedia, IEEE Signal Processing Letters, and is currently serving as an associate editor for IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Broadcasting and IEEE Circuits and Systems Society Newsletter. Besides, he is IEEE Distinguished Lecturer for 2009-2013, and a steering committee member of IEEE Transactions for Mobile Computing from 2011-2013.

 

Dr Aimin Jiang, PhD (invited speaker)
Hohai University (China)
and Professor H. K. Kwan, PhD, DIC, FIET, SrMIEEE, PEng (invited speaker)
University of Windsor (Canada)

Speech Title: Recent Advances in Sparse FIR Filter Design using l0/l1 Optimization Techniques

Abstract:
Lately, much effort has been made to develop efficient algorithms for low complexity FIR filter design. A sparse FIR filter contains a large number of zero coefficients, such that multipliers and adders corresponding to these zero coefficients are not required, resulting in a considerable reduction in hardware cost and power consumption. In this talk, the characteristics of sparse FIR filter design problems will be analyzed. In particular, sparse FIR filter design is to be compared to sparse coding. Although these two classes of problems have some essential connections, it can be shown that they have distinct properties. In view of this point, researchers tend to develop more complicated techniques, other than directly utilize classical sparse coding algorithms, for sparse FIR filter design. In the talk, some typical sparse FIR filter design algorithms based on l0/l1 optimization techniques will be reviewed, their merits analyzed, and their performance evaluated through design examples.

Aimin Jiang received the B.E. and M.E. degrees from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2001 and 2004, respectively, and the Ph.D. degree from University of Windsor, Windsor, Canada, in 2010. They are all in Electrical Engineering. During 2014-2016, he worked as a senior software engineer in Fortemedia (Nanjing) Ltd. Currently, he serves as a professor in the College of Internet of Things Engineering, Hohai University, China. His research interests include mathematical optimization, numerical algorithms, and a variety of their applications to digital signal processing and communications, e.g., digital filter design, sparse representation of signals, low rank approximation. Dr. Jiang is currently a member of the Digital Signal Processing Technical Committee of the IEEE Circuits and Systems Society.

H. K. Kwan received his D.I.C. and Ph.D. degree in Electrical Engineering (Signal Processing) in 1981 from the Imperial College London, United Kingdom. His previous experience includes working as a design engineer in electronics and computer memory industry in Hong Kong during 1977-78; and serving as a faculty member (Lecturer) in the Department of Electronic Engineering in The Hong Kong Polytechnic University during 1981, and then in the Department of Electrical and Electronic Engineering in The University of Hong Kong during 1981-88. He subsequently joined the University of Windsor as an Associate Professor and holds the rank of Professor in Electrical and Computer Engineering since 1989.
He has published extensively on digital filters and intelligent systems in refereed journals and conference proceedings. The innovations described in his research papers have benefited (and/or been utilized by) industry in developing various inventions described in 8 US and 6 European patents. He has taught a variety of undergraduate and graduate courses and his recent teaching covers subject areas of Multimedia Signals and Systems, Intelligent Signal Processing, Intelligent Computing, Computational Intelligence.

He has served in a variety of capacities including chair and member in various undergraduate, graduate, administrative, faculty, and university committees; advisor, appraiser, assessor, reviewer, external examiner, and editorial board member of various academic and professional tasks; chair, organizer, and member of technical program committees and sessions in various international, national, and regional conferences, symposia, and workshops; and the past-chair, chair, chair-elect, secretary, secretary-elect, and member of the Digital Signal Processing Technical Committee and the Neural Systems and Applications Technical Committee of the IEEE Circuits and Systems Society.

Dr. Kwan has been a recipient of research grants from sources including NSERC, Auto21, and Micronet; a recipient of research professorship, research excellence, research fellowship, and outstanding paper awards; a licensed Professional Engineer (Ontario), a Chartered Electrical Engineer (UK), and was elected in 1996 a Fellow of the Institution of Engineering and Technology (UK).