An-Yeu (Andy) Wu
Compressive sensing (CS) Circuits and Systems for Intelligent Biomedical Signal Processing
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Abstract: Compressive sensing (CS) is a promising solution for physiological signals acquisition and wireless healthcare systems. It enables new reduced-complexity designs of sensor nodes and helps to save overall transmission power in wireless sensor network. However, in practical applications, measurement noise from non-ideality of CS sensor destroy the signal sparsity, thus drastically degrading the quality of the reconstructed signals. We find that sparsity information/estimation is the key factor to cope with measurement noise. However, prior data information, such as sparsity level or noise level, is usually unavailable in the CS-based wireless healthcare system. In this talk, we will first give an overview of the CS techniques, including the fundamentals and the popular reconstruction algorithms (BP, OMP). Then, we present a robust mechanism of sparsity estimation, called Sparsity Estimation-Subspace Pursuit (SE-SP). It can reconstruct compressively-sensed physiological signals in the presence of measurement noise. The experimental results show that the SE-SP shows superior robustness against measurement noise. A high-efficient CS reconstruction chip is also implemented based on the SE-SP algorithm, which was presented in 2018 ISSCC. We will exploit the embedded security feature of CS-based transmission. CS sensors can generate randomized measurement data during the sub-sampling process. Hence, it bears natural security for those sensed data. In this talk, we will present a new mechanism to enhance the security level of CS data. The two topics presented in this talk are applicable to emerging CS-based wireless healthcare systems.
Bio: An-Yeu (Andy) Wu (IEEE M’96-SM’12-F’15) received the B.S. degree from National Taiwan University in 1987, and the M.S. and Ph.D. degrees from the University of Maryland, College Park in 1992 and 1995, respectively, all in Electrical Engineering.
In August 2000, he joined the faculty of the Department of Electrical Engineering and the Graduate Institute of Electronics Engineering, National Taiwan University (NTU), where he is currently a Professor. His research interests include low-power/high-performance VLSI architectures for DSP and communication applications, adaptive/ bio-medical signal processing, reconfigurable broadband access systems and architectures, and System-on-Chip (SoC)/Network-on-Chip (NoC) platform for software/hardware co-design. He has published more than 270 refereed journal and conference papers in above research areas, together with six book chapters and 24 granted US patents.
From August 2007 to Dec. 2009, he was on leave from NTU and served as the Deputy General Director of SoC Technology Center (STC), Industrial Technology Research Institute (ITRI), Hsinchu, TAIWAN, supervising WiMAX, Parallel Core Architecture (PAC) VLIW DSP Processor, and Android-based Multicore SoC platform projects. From March 2014 to September 2017, Dr. Wu was the Director of national talent cultivation program office in National Program for Intelligent Electronics (NPIE), under sponsorship of Ministry of Education in Taiwan.
In 2015, Prof. Wu was elevated to IEEE Fellow for his contributions to “DSP algorithms and VLSI designs for communication IC/SoC.” He serves as a Board of Governor (BoG) Member in IEEE Circuits and Systems Society (CASS) for two terms (2016-2018, 2019-2021). From August 2016 to July 2019, he served as the Director of Graduate Institute of Electronics Engineering (GIEE), National Taiwan University. He now serves as Editor-in-Chief (EiC) of IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS). Recently, he received 2019 ECE Distinguished Alumni Award from ECE department of University of Maryland (UMD), and 2019 Outstanding Engineering Professor Award, from the Chinese Institute of Engineers (CIE), Taiwan.
Approximate Computing: Test and Reliability issues and opportunities
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Abstract: Approximate Computing (AxC) is today one of the hottest topics related to system design and optimization. Thanks to this computing paradigm, designers are able to reduce area, power consumption, and even production costs in the case the target application can accept a given degree of inaccuracy in the final computations. This presentation discusses the impact of Approximate Computing on the test and reliability. More in particular, it aims at showing that it is possible to use Approximate Computing to implement low cost but still efficient test mechanisms and fault tolerant architectures to be used in safety-critical applications.
Bio: Alberto Bosio received the PhD in Computer Engineering from the Politecnico di Torino, Italy in 2006. From 2007 to 2018 he was an Associate Professor at LIRMM – University of Montpellier in France. Hi is now a Full Professor the INL – Ecole Centrale de Lyon, France. His research interests include Approximate Computing, In-Memory Computing, Test and Diagnosis of Digital circuits and systems and Reliability. He co-authored 1 book, 3 patents 35 journals, and over 120 conference papers. He is the chair of the ETTTC. He is a member of the IEEE.
Future Human: Merging Minds and Machines
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Abstract: It appears the race is now on to merge minds and machines. For decades, scientists, engineers and clinicians have been developing innovative neurotechnologies for studying the human brain, and to “repair” injuries or treat neurological disease. More recently, the field has attracted interest and significant investment from industry for consumer applications, some with ambitious visions towards augmented intelligence. Relentless technological progress is however outpacing advances in our fundamental understanding of what some call “the final frontier in science”, the human brain. New tools developed can provide the opportunity to accelerate this mission. This keynote will unwrap some of the CAS technologies that are making this possible and explore some of what may be coming our way.
Bio: Dr Timothy Constandinou is a Reader in Neural Microsystems at Imperial College London. He leads the Next Generation Neural Interfaces (NGNI) Lab at Imperial. His group creates innovative neurotechnologies to enable communication between the nervous system and electronic devices – for research tools and medical devices. He additionally leads the “Biosensors and Medical Device Technologies” group within the UK Dementia Research Institute, Care Research & Technology Centre. Within the IEEE he currently serves on the BRAIN Initiative Steering Committee, IEEE CASS Sensory Systems and IEEE CASS Biomedical Circuits & Systems Technical Committees and is the Deputy Editor-in-Chief of IEEE Trans. Biomedical Circuits & Systems (TBioCAS) for the 2020-21 term. He previously served on several conference committees (e.g. Technical Program Committee Co-Chair BioCAS 2011, 2012, 2018, General Chair of BrainCAS/NeuroCAS 2016, 2018), the IEEE Circuits & Systems Society (CASS) Board of Governors for the term 2017-19, and co-chaired the steering group of the Royal Society iHuman perspective on Neural Interfaces and the Ecosystem.
Software-Defined Radio Education and the Next Generation of Wireless Communications Innovators
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Abstract: Software-Defined Radio (SDR) technology is a powerful prototyping tool used for the design and development of wireless proof-of-concept systems. Over the past decade, the rapid evolution of computing hardware, radio frequency front-ends (RFFEs), and software development environments have yielded SDR platforms that are versatile, cost-effective, and computationally powerful; SDR are capable of implementing anything from simple wireless spectrum energy detectors to complete/operational 5G base stations. At the same time, much of undergraduate and graduate curricula focused on wireless communication systems engineering found around the world is still mostly focused on theoretical concepts and not bridging these lessons with real-world examples with hands-on experiments and projects. In this keynote talk, I will present several lessons learned regarding an educational paradigm that teaches wireless communication systems engineering from a more holistic perspective, where both theoretical concepts and practical hands-on learning are combined together such that the next-generation of wireless communications innovators are prepared to enter the workforce. Starting with an overview of how to introduce the concept of the “analog/digital divide” in a modern communication system to an undergraduate student, the presentation describes the logic behind the choice of several hands-on experiments using SDR designed to reinforce concepts taught in class. Finally, the use of SDR in senior design capstone projects, as well as MS thesis and PhD dissertation research, as a tool for solving challenging problems and the construction of proof-of-concepts is presented. All experiences and information presented in this talk are based on the nearly 13 years of SDR undergraduate and graduate education conducted at Worcester Polytechnic Institute.
Bio: Dr. Alexander M. Wyglinski is an internationally recognized expert in wireless communications, cognitive radio, 5G, connected vehicles, software-defined radio, dynamic spectrum access, satellite communications, vehicular technology, wireless system optimization and adaptation, autonomous vehicles, and cyber-physical systems. Dr. Wyglinski is a Full Professor of Electrical and Computer Engineering and a Full Professor of Robotics Engineering (courtesy appointment) at Worcester Polytechnic Institute, Worcester, MA, USA, as well as the Director of the Wireless Innovation Laboratory (WI Lab). Dr. Wyglinski is very active in the technical community, serving on the organizing committees of numerous technical conferences and several journal editorial boards. These activities include serving as the General Co-Chair for the 82nd IEEE Vehicular Technology Conference in Fall 2015, as well as Technical Editor of the IEEE Communications Magazine. From January 2018 to December 2019, Dr. Wyglinski served as the President of the IEEE Vehicular Technology Society, an applications-oriented society of approximately 5000 members that focuses on the theoretical, experimental, and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles, and land transportation. Throughout his academic career, Dr. Wyglinski has published approximately 45 journal papers, over 120 conference papers, nine book chapters, and three textbooks. He is currently being or has been sponsored by organizations such as The MathWorks, Toyota InfoTechnology Center U.S.A., Defense Advanced Research Projects Agency, Naval Research Laboratory, MITRE Corporation, MIT Lincoln Laboratory, Office of Naval Research, Air Force Research Laboratory Space Vehicles Directorate, and the National Science Foundation. Dr. Wyglinski is a Senior Member of the IEEE, as well as a member of Sigma Xi, Eta Kappa Nu, and the ASEE.