Prof. Robert Minasian, IEEE & OSA Fellow, The University of Sydney, Australia
Professor Minasian is a Chair Professor with the School of Electrical and Information Engineering at the University of Sydney, Australia. He is also the Director of the Fibre-optics and Photonics Laboratory. His research has made key contributions to microwave photonic signal processing. He is recognized as an author of one of the top 1% most highly cited papers in his field worldwide. Professor Minasian has contributed over 370 research publications, including Invited Papers in the IEEE Transactions and Journals, and Plenary and Invited papers at leading international conferences. Professor Minasian was the recipient of the ATERB Medal for Outstanding Investigator in Telecommunications, awarded by the Australian Telecommunications and Electronics Research Board. He is a Life Fellow of the IEEE, and a Fellow of the Optical Society of America.
Speech Title: Microwave photonic signal processing and sensing
Abstract: Photonic signal processing offers the prospect of overcoming a range of challenging problems in the processing of high-speed signals. Its intrinsic advantages of high time-bandwidth product and immunity to electromagnetic interference (EMI) have led to diverse applications. Photonic signal processing leverages the advantages of the optical domain to benefit from the wide bandwidth, low loss, and natural EMI immunity that photonics offers. Next generation global telecommunication platforms and emerging applications in radar, communications and sensing will require entirely new technologies to address the current limitations of electronics for massive capacity and connectivity. Microwave photonics, which merges the worlds of RF and photonics, shows strong potential as a key enabling technology to obtain new paradigms in the processing of high speed signals that can overcome inherent electronic limitations. In addition, the growth of silicon photonics allows integration together with CMOS electronics, to obtain future signal processing systems that can implement high bandwidth, fast and complex functionalities. Recent advances in microwave photonic signal processing are presented. These includes versatile beamforming and beam steering systems for phased array antennas, single bandpass microwave photonic filters, photonic-assisted scanning receivers for microwave frequency measurement, and microwave photonic sensing systems. These microwave photonic processors provide new capabilities for the realisation of high-performance signal processing and sensing.
Prof. Ho Pui, Aaron HO, SPIE Fellow, The Chinese University of Hong Kong (CUHK), Hong Kong
Dr. Ho received his BEng and PhD in Electrical and Electronic Engineering from the University of Nottingham in 1986 and 1990 respectively. Currently a professor in the Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK), he has held positions as Associate Dean of Engineering, CUHK, Assistant Professor in the Department of Physics and Materials Science, City University of Hong Kong, and Senior Process Engineer for semiconductor laser fabrication in Hewlett-Packard. Started as a compound semiconductor materials scientist, his current academic interests focus at nano-sized semiconductor materials for photonic and sensor applications, optical instrumentation, surface plasmon resonance biosensors, lab-on-a-chip and biophotonics. He has published over 300 peer-reviewed articles, 16 Chinese and 6 US patents. He is a Fellow of SPIE and HKIE, and a senior member of IEEE.
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Prof. Kunbao Cai, Chongqing University, China
Dr. Kunbao Cai was born in Shanghai City of China, in 1950. He graduated from the Department of Electrical Engineering, Shanghai Jiao Tong University, China, in 1975, and received the M.E. degree in 1983 and the Ph.D. degree in 1998, all in electrical engineering, from Chongqing University, China. From 1978 to 1980, he assisted teaching in the Electronic Department, Shanghai Jiao Tong University. From 1991 to 1994, he assisted researching on signal processing and system identification, and then studied, in the Department of Biomedical Engineering, McGill University, Canada. He held the following teaching and research positions in Chongqing University: Teaching Assistant, 1983-1986; Lecturer of Electrical Engineering, 1986-1994; Associate Professor of Electrical Engineering, 1994-2000; Full Professor of Electrical Engineering, from 2000. He retired from Chongqing University in 2015. His major research interests include digital signal processing, biomedical signal processing, and artificial neural network with application to biomedical engineering. He is the author of textbooks: Digital Signal Processing (English Editions I and II), Publishing House of Electronics Industry, Beijing, China, (2007 and 2011). He completed a number of teaching research projects: Chongqing municipal excellent course of Signals and Linear Systems (from 2006), appointed as a Chief Prof.; Chongqing municipal excellent course of Digital Signal Processing (from 2008), appointed as a main Prof.; national bilingual teaching demonstration course of Signals & Systems (from 2010), appointed as a Chief Prof. Also he received a number of awards at Chongqing University for excellent teaching and textbook publications.
Speech Title: Transforms of Multiwavelet and Multiwavelet Packet with Application in Identifying Heroin Addict Pulse Signals
Abstract: It is well known that the multiwavelets are a natural generalization of the scalar wavelets and can be viewed as vector-valued wavelets which have several advantages in comparison to scalar wavelets. Correspondingly, the multiwavelet transforms can provide more adaptive to satisfy the requirements of a variety of signal analysis. On the other hand, the multiwavelet transforms have also a fast computational structure for multiresolution analysis, which can be viewed as a generalization of the fast algorithm of Mallat’s multiresolution analysis for the case of scalar discrete wavelet transforms. However, while using the Mallat’s multiresolution analysis method to realize a multiwavelet transform, only the decomposed lowpass component at a decomposition stage is further decomposed, and the highpass component is left unchanging further. Therefore, the multiwavelet transforms can not supply finer time-frequency localized information for high frequency component obtained at every decomposition stage. Naturally, the concept of wavelet packet transforms was introduced into the multiwavelet transforms, which led to the so-called multiwavelet packet transforms. Thus, both the lowpass and highpass components at any decomposition stage can be further decomposed, with the result that any finer degree of the time-frequency localization can be obtained. It is really a great interesting to explore the effectiveness of these two modern signal processing techniques in identifying heroin addict pulse signals. In the research, the transforms of multiwavelet and multiwavelet packet are, respectively, used to decompose pulse signals collected from 15 heroin addicts and 15 healthy normal subjects. Combining entropy techniques in the feature extraction, the feature vectors have good distributive properties in feature plane. To obtain a good generalization for classification of two classes of pulse signals, the vector support machine is introduced. It is expected to receive good research results.
Assoc. Prof. Waleed Habib Abdulla, The University of Auckland, New Zealand
Dr. Waleed Abdulla received his PhD Degree from Otago University in New Zealand in 2002. He is currently Associate Professor in the University of Auckland/New Zealand. He served as Vice President- Member Relations and Development in Asia Pacific Signal and Information Processing Association (APSIPA) for two terms followed by 2-year Board of Governors. He is one of the steering committee members who established APSIPA in 2009. He is the APSIPA Newsletter founder and was Editor-in-Chief. He visited and delivered talks in several universities and conferences as presenter and keynote speaker. He has been serving as an editorial board member of 5 journals. He supervised over 30 PhD and Master Degrees students. He was awarded APSIPA Distinguished Lecturer Award, University of Auckland Faculty Best Teachers of the Year in 2005 and 2012. His research activities are under “Signal Processing, Analysis, and Recognition”, which encompass multidisciplinary topics. He focuses on fundamental and applied research in domains with direct communal relevance including, human health and well-being and economic impact. Specific recent research activities with PhD students are in: Speech Enhancement, Speaker Recognition, Speech Processing, Hyperspectral Imaging for detecting Honey Botanic Origins, Diagnosing Diabetic Retinopathy, Active Noise Control, Human Biometrics, Lase Like Ultrasound Signal Communication. He won two best paper awards in 2012 and 2016 in two major conferences. He co-authored a book in Audio Watermarking, which has been downloaded over 7500 times. The book includes many topics in the psychology of hearing.
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