Virtual Seminar by Ekram Hossain

Title: Federated Learning in Unreliable and Resource-Constrained Cellular Wireless Networks

Date: May 26, 2021; Time: 11AM EDT

Registration: Please register at https://albany.zoom.us/meeting/register/tJYvd-irrDMuH9ImDFQ65_9LugOGR4J-fEBg

Abstract: Federated learning is a machine learning setting where the centralized location trains a learning model by using remote devices. Federated learning algorithms cannot be employed in wireless networks unless the unreliable and resource-constrained nature of the wireless medium is taken into account. In this talk, I shall present a federated learning algorithm that is suitable for cellular wireless networks in a real-world scenario. I shall discuss its convergence properties, and the effects of local computation steps and communication steps on its convergence. Through experiments on real and synthetic datasets, I shall demonstrate the convergence of the proposed algorithm.

Bio: Ekram Hossain (IEEE Fellow) is a Professor in the Department of Electrical and Computer Engineering at University of Manitoba, Winnipeg, Canada. He is a Member (Class of 2016) of the College of the Royal Society of Canada, a Fellow of the Canadian Academy of Engineering, and also a Fellow of the Engineering Institute of Canada (http://home.cc.umanitoba.ca/~hossaina). He received his Ph.D. in Electrical Engineering from University of Victoria, Canada, in 2001. Dr. Hossain’s current research interests include design, analysis, and optimization of wireless communication networks (with emphasis on beyond 5G/6G cellular), applied machine learning and game theory, and network economics. He was elevated to an IEEE Fellow “for contributions to spectrum management and resource allocation in cognitive and cellular radio networks”. He was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2017, 2018, 2019, and 2020. Dr. Hossain has won several research awards including the “2017 IEEE Communications Society Best Survey Paper Award, the 2011 IEEE Communications Society Fred Ellersick Prize Paper Award, University of Manitoba Merit Award in 2010, 2013, 2014, and 2015 (for Research and Scholarly Activities), and the IEEE Wireless Communications and Networking Conference 2012 (WCNC’12) Best Paper Award. He received the 2017 IEEE ComSoc TCGCC (Technical Committee on Green Communications & Computing) Distinguished Technical Achievement Recognition Award “for outstanding technical leadership and achievement in green wireless communications and networking”. Currently he serves as the Editor-in-Chief of the IEEE Press and an Editor for IEEE Transactions on Mobile Computing. Previously, he served as an Area Editor for the IEEE Transactions on Wireless Communications in the area of “Resource Management and Multiple Access” (2009-2011) and an Editor for the IEEE Journal on Selected Areas in Communications – Cognitive Radio Series (2011-2014). He serves as the Director of Magazines for the IEEE Communications Society (2020-2021). Dr. Hossain was an elected Member of the Board of Governors of the IEEE Communications Society for the term 2018-2020. He is a Distinguished Lecturer of the IEEE Communications Society. He is a registered Professional Engineer in the province of Manitoba, Canada.

About the Monthly Virtual Seminar Series: The IEEE TCCN Special Interest Group for AI and Machine Learning in Security conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

 

Virtual Seminar by Gene Tsudik

Title: Secure Code Execution on Untrusted Remote Devices

Date: April 28, 2021; Time: 1PM EDT

Registration: Please register using the following link. You will receive a link in your email to attend the talk online.
https://forms.gle/bTah3LEyV5vUxMAw7

Abstract: Our society is increasingly reliant upon a wide range of Cyber-Physical Systems (CPS), Internet-of-Things (IoT), embedded, and so-called “smart” devices. They often perform safety-critical functions in numerous settings, e.g., home, office, medical, automotive and industrial. Some devices are small, cheap and specialized sensors and/or actuators. They tend to have meager resources, run simple software, sometimes upon “bare metal”. If such devices are left unprotected, consequences of forged sensor readings or ignored actuation commands can be catastrophic, particularly, in safety-critical settings. This prompts the following three questions: (1) How to trust data produced by a simple remote embedded device? (2) How to ascertain that this data was produced via execution of expected software? And, (3) Is it possible to attain (1) and (2) under the assumption that all software on the remote device might be modified or compromised? In this talk, we answer these questions by describing APEX: (Verified) Architecture for Proofs of Execution, the first of its kind result for low-end embedded systems. This work has a range of applications, especially, to authenticated sensing and trustworthy actuation, APEX incurs low overhead, making it affordable even for lowest-end embedded devices; it is also publicly available.

Bio: Gene Tsudik is a Distinguished Professor of Computer Science at the University of California, Irvine (UCI). He obtained his PhD in Computer Science from USC in 1991. Before coming to UCI in 2000, he was at the IBM Zurich Research Laboratory (1991-1996) and USC/ISI (1996-2000). His research interests include many topics in security, privacy and applied cryptography. Gene Tsudik is a Fulbright Scholar, Fulbright Specialist (twice), a fellow of ACM, IEEE, AAAS, IFIP and a foreign member of Academia Europaea. From 2009 to 2015 he served as Editor-in-Chief of ACM Transactions on Information and Systems Security (TISSEC, renamed TOPS in 2016). Gene was the recipient of 2017 ACM SIGSAC Outstanding Contribution Award. He is also the author of the first crypto-poem published as a refereed paper.

About the Monthly Virtual Seminar Series:

The IEEE TCCN Security Special Interest Group conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

Virtual Seminar by Zhu Han

Title: MetaSensing: Reconfigurable intelligent surface Assisted RF 3D Sensing using Machine Learning

Time and Date: March 30, 2021 at 9:00AM EDT

Presenter:  Professor Zhu Han, University of Houston, USA

Venue: online registration via https://www.eventbrite.com/e/ieee-comsoc-tccn-seminar-by-prof-zhu-han-tickets-147491163039?ref=estw (Zoom meeting link will be provided prior to the seminar)

Abstract: Reconfigurable intelligent surface (RIS) stands out as a novel approach to improve the communication and sensing in the future wireless networks. It is capable to actively shape the uncontrollable wireless environments into a desirable form via flexible phase shift reconfiguration without extra hardware or power costs. To better exploit the potential of such a technique, it is essential to develop distributed configuration, to design new protocols, to explore and implement suitable application scenarios, as well as to perform intelligent control and orchestration. First we provide a general introduction of the intelligent meta-surface along with the state-of-the-art research in different areas. Then we introduce the unique features of intelligent meta-surface which enlighten its broad applications to communication and sensing, in a comprehensive way. Related design, analysis, optimization, and signal processing techniques will be presented. Finally, we explore typical meta-surface applications and discuss implementation issues with an emphasis on high-resolution smart RF sensing. Formalized analysis of several up-to-date challenges and technical details on system design will be provided for different applications.

Bio: Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland. From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor in Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in Electrical and Computer Engineering Department as well as Computer Science Department at University of Houston, Texas. His research interests include security, wireless resource allocation and management, wireless communication and networking, game theory, and wireless multimedia. Dr. Han is an NSF CAREER award recipient 2010. Dr. Han has several IEEE conference best paper awards, and winner of 2011 IEEE Fred W. Ellersick Prize, 2015 EURASIP Best Paper Award for the Journal on Advances in Signal Processing and 2016 IEEE Leonard G. Abraham Prize in the field of Communication Systems (Best Paper Award for IEEE Journal on Selected Areas on Communications). Dr. Han is the winner 2021 IEEE Kiyo Tomiyasu Award. He has been IEEE fellow since 2014, AAAS fellow since 2020 and IEEE Distinguished Lecturer from 2015 to 2018. Dr. Han is 1% highly cited researcher according to Web of Science since 2017.

Virtual Seminar by Yalin Sagduyu

Title: Adversarial Machine Learning for Wireless Security in 5G and Beyond

Date and Time: March 26, 2021 at 10AM ET

Registration Process: Please register using the following link. You will receive a link in your email to attend the talk online.

https://forms.gle/krrmynfr3DDH7ENS9

Abstract: Machine learning provides powerful means to learn from the dynamic spectrum environment and solve complex tasks for wireless communications. Supported by recent advances in algorithmic and computational capabilities, deep learning has emerged as a viable solution to efficiently utilize the limited spectrum resources and optimize wireless communications, with 5G and beyond enhancements to meet the ever-growing demands for high-rate and low-latency communications. As deep learning is becoming a key component in emerging wireless technologies, a new security threat arises due to adversarial machine learning that exploits the vulnerabilities of deep learning to adversarial manipulations. Adversarial machine learning has been applied to different data domains ranging from computer vision to natural language processing. By considering the unique characteristics of the wireless medium, this talk will present adversarial machine learning as a new attack surface for the next-generation communication systems. Novel attack and defense mechanisms built upon adversarial machine learning will be described with examples from signal classification, dynamic spectrum access, and 5G and beyond applications related to spectrum co-existence, user authentication, covert communications, and network slicing. Research challenges and directions will be discussed for effective and safe adoption of much-needed machine learning techniques in the emerging wireless technologies.

Bio: Dr. Yalin Sagduyu is the Director of Networks and Security Division at Intelligent Automation, Inc. (IAI). He received his Ph.D. degree in Electrical and Computer Engineering from University of Maryland, College Park. At IAI, he directs a division of over 50 research scientists and engineers, and executes a broad portfolio of R&D projects on wireless communications, networks, security, machine learning, adversarial machine learning, and 5G and beyond. He has been a Visiting Research Professor in the Electrical and Computer Engineering Department of University of Maryland, College Park. He served as a Conference Track Chair at IEEE PIMRC, IEEE GlobalSIP and IEEE MILCOM, and in the organizing committee of IEEE GLOBECOM. He organized and chaired workshops at IEEE CNS, IEEE ICNP, ACM Mobicom, and ACM WiSec. He received the Best Paper Award at IEEE HST.

About the Monthly Virtual Seminar Series:

The IEEE TCCN Security Special Interest Group conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

Virtual Seminar by Wade Trappe

Title: A Quick Look at New Risks Facing Wireless Systems

Date and Time: February 25, 2021 at 10AM ET

Registration Process: Please register using the following link. You will receive a link in your email to attend the talk online.

https://forms.gle/omTft4DCuuGVtdDz7

Abstract: Wireless networks are susceptible to a wide range of security risks. The evolution from old wireless technologies, such as3G and 802.11, to newer technologies, such as 5G and mmWave, hasnot fundamentally changed the core challenges that undermines the security of wireless networks: Wireless systems are easy to access,the wireless medium is easy to broadcast and eavesdrop on, and the increasingly pervasive nature means that we are becoming increasingly reliant on them for day-to-day functions. This talk will examine a broad sampling of wireless-based threats that will likely become more prevalent as we move towards the next generation of wireless system. These systems are characterized by a closer integration between communications, computation, and the real world. As such, the challenges we face to secure these systems requires that wireless engineers and systems developers think more holistically about how they will design and implement security mechanisms. In short, we must really work to protect our systems “across the stack” and even “into the application.”

Bio: Wade Trappe is a Professor in the Electrical and Computer Engineering Department at Rutgers University, and Associate Director of the Wireless Information Network Laboratory (WINLAB), where he directs WINLAB’s research in wireless security. He has led several federally funded projects in the area of cybersecurity and communication systems, projects involving security and privacy for sensor networks, physical layer security for wireless systems, a security framework for cognitive radios, the development of wireless testbed resources (the ORBIT testbed, www.orbit-lab.org), and new RFID technologies. He was the principal investigator for the original DARPA Spectrum Challenge, in which teams battled for spectrum superiority against each other on the ORBIT testbed arena. His experience in network security and wireless spans over 20 years, and he has co-authored a popular textbook in security, Introduction to Cryptography with Coding Theory, as well as several monographs on wireless security, including Securing Wireless Communications at the Physical Layer and Securing Emerging Wireless Systems: Lower-layer Approaches.

About the Monthly Virtual Seminar Series:

The IEEE TCCN Security Special Interest Group conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

Virtual Seminar by Rose Qingyang Hu

Title: AI and Machine Leaning in Spectrum Sharing Security

Date and Time: January 29, 2021 at 10AM ET

Registration Process: Please register using the following link. You will receive a link in your email to attend the talk online.

https://forms.gle/Ngay2ZvoF4yqEWgCA

Abstract: Dynamic spectrum sharing has been widely considered a key enabler of supporting future wireless networks for massive connectivity and pervasive communications. The complexity and dynamics of the spectrum sharing systems are being exposed to various new attacks, which require novel security and protecting mechanisms that are adaptive, reliable, and scalable. Artificial intelligence and Machine learning based methods have been widely explored to address these issues. In this talk, we will present the recent research advancements in AI/ML based spectrum sharing as well as the corresponding security mechanisms. In particular, we will focus on the state-of-art methodologies for improving the performance of the spectrum sharing communication systems by using AI/ML in different sharing paradigms such as cognitive radio networks, Licensed shared access/spectrum access systems, LTE-U/LAA networks, and ambient backscatter networks. How AI and ML are used to tackle spectrum sharing specific security issues such as primary user emulation attacks, spectrum sensing data falsification attacks, jamming/eavesdrop attacks, privacy issues, as well as how AL/ML can be possibly exploited to launch adversarial attacks in the spectrum sharing systems will be further elaborated. We expect that this talk will highlight the challenges as well as research opportunities in exploring AI and ML techniques to support the ever increasingly important yet complicated spectrum sharing as well as the related security mechanisms.

Bio: Rose Qingyang Hu currently is a Professor of Electrical and Computer Engineering Department and Associate Dean for Research of College of Engineering at Utah State University. Besides more than 12 years’ academia research experience, Prof. Rose Hu has more than 10 years R&D experience with Nortel, Blackberry and Intel as technical manager, senior research scientist, and senior wireless system architect, leading industrial 3G and 4G technology development, 3GPP/IEEE standardization, system level simulation and performance evaluation. Her current research interests include next-generation wireless communications, wireless network design and optimization, Internet of Things and Cyber Physical System, AI/ML, Mobile Edge Computing, wireless security. She has published over 260 papers in leading IEEE journals and conferences and holds over 30 patents in her research areas. Prof. Rose Hu is a Fellow of IEEE, NIST Communication Technology Laboratory Innovator 2020, IEEE Communications Society Distinguished Lecturer 2015-2018, IEEE Vehicular Technology Society Distinguished Lecturer 2020 – 2022, member of Phi Kappa Phi honor society, and recipient of Best Paper Awards from IEEE Globecom 2012, IEEE ICC 2015, IEEE VTC Spring 2016, and IEEE ICC 2016. She serve as TPC Co-Chair for IEEE ICC 2018 and TPC Co-Chair for IEEE Globecom 2023. She is currently serving on the editorial boards for IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, IEEE Communications Magazine, IEEE Wireless Communications Magazine.

About the Monthly Virtual Seminar Series:

The IEEE TCCN Security Special Interest Group conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

Virtual Seminar by Kaushik Chowdhury

Title: Deep Convolutional Neural Networks for Device Identification

Date and Time: December 16 at 9AM ET

Registration Process: Please register using the following link. You will receive a link in your email to attend the talk online.

https://forms.gle/odnKNA7EVoKXZdRz5

Abstract: Network densification is poised to enable the massive throughout jump expected in the era of 5G and beyond. In the first part of the talk, we identify the challenges of verifying identity of a particular emitter in a large pool of similar devices based on unique distortions in the signal, or ‘RF fingerprints’, as it passes through a given transmitter chain. We show how deep convolutional neural networks can uniquely identify a radio in a large signal dataset composed of over a hundred WiFi radios with accuracy close to 99%. For this, we use tools from machine learning, namely, data augmentation, attention networks and deep architectures that have proven to be successful in image processing and modify these methods to work in the RF-domain. In the second part of the talk, we show how intentional injection of distortions and carefully crafted FIR filters applied to the transmitter-side can help in enhanced classification. Finally, we discuss how to detect new devices not previously seen during training using observed statistical patterns. We conclude by showing a glimpse of other applications of RF fingerprinting, like 5G waveform detection in large-scale experimental platforms and identifying a specific UAV in a swarm.

Bio: Kaushik Chowdhury is Professor and Faculty Fellow in the ECE department and Associate Director at the Institute for the Wireless IoT at Northeastern University, Boston. He was awarded the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2017, the DARPA Young Faculty Award in 2017, the Office of Naval Research Director of Research Early Career Award in 2016, and the NSF CAREER award in 2015. He has received best paper awards at several conferences that include, Infocom, Globecom, ICC (3x), SenSys, ICNC, and DySpan. He is presently a co-director of the Platforms for Advanced Wireless Research (PAWR) project office and the Colosseum RF emulator. His current research interests span applied machine learning to wireless systems, networked robotics, wireless charging and at-scale experimentation for emerging 5G and beyond networks.

About the Monthly Virtual Seminar Series:

The IEEE TCCN Security Special Interest Group conducts a monthly virtual seminar series to highlight the challenges in securing the next generation (xG) wireless networks. The talks will feature cutting edge research addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

Virtual Seminar #5

Dear TCCN fellow members, 

Please find the details of the fifth virtual seminar.

Time and date: EDT 9:00am-10:00am, Wednesday, 18 November 2020

Venue: online registration via https://www.eventbrite.co.uk/e/free-webinar-secure-computation-with-privacy-preservation-for-cps-tickets-125578208803

Title: Secure Computation with Privacy Preservation for Cyber Physical System Applications

Presenter:  Professor Zhu Han, University of Houston, USA

Abstract: Cyber Physical System (CPS) have infiltrated into many areas such as aerospace, automobiles, chemical processing, civil infrastructure, energy, healthcare, transportation, entertainment, and consumer appliances due to their tight integration of computation and networking capabilities to monitor and control the underlying systems. Many domains of CPS such as smart metering, sensor/data aggregation, crowd sensing, traffic control etc., typically collect huge amounts of individual information for data analysis and decision making, therefore privacy is a serious concern in CPS. Most of the traditional approaches protect the privacy of individual’s data by employing trusted third parties or entities for data collection and computation. An important challenge in these large-scale distributed applications is how to protect the privacy of the participants during computation and decision making, especially when such third party entities are untrusted. Considering various CPS applications involving modeling, we first discuss on utilizing applied cryptographic techniques for privacy preserving secure computation. Then we focus on the differential privacy based secure computation that guarantees individual privacy in presence of untrusted third party entities. Since confidential information must not be inappropriately released, and the use of untrusted information must not corrupt trusted computation and the utility. This talk concludes by focusing on the development of such tools for state-of-the-art applications by considering application-specific information security requirements.

Bio:  Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland. From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor in Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in Electrical and Computer Engineering Department as well as Computer Science Department at University of Houston, Texas. His research interests include security, wireless resource allocation and management, wireless communication and networking, game theory, and wireless multimedia. Dr. Han is an NSF CAREER award recipient 2010. Dr. Han has several IEEE conference best paper awards, and winner of 2011 IEEE Fred W. Ellersick Prize, 2015 EURASIP Best Paper Award for the Journal on Advances in Signal Processing and 2016 IEEE Leonard G. Abraham Prize in the field of Communication Systems (Best Paper Award for IEEE Journal on Selected Areas on Communications). Dr. Han is the winner 2021 IEEE Kiyo Tomiyasu Award. He has been IEEE fellow since 2014, AAAS fellow since 2020 and IEEE Distinguished Lecturer from 2015 to 2018. Dr. Han is 1% highly cited researcher according to Web of Science since 2017.


Best regards,
Yue Gao
Chair, Technical Committee on Cognitive Networks (TCCN)

Virtual Seminar by Prof. Vincent Poor

Dear Colleagues,

The IEEE TCCN Security Special Interest Group is launching a monthly virtual seminar series hosting speakers to highlight the challenges in securing the next generation (xG) wireless networks. The theme of the talks will feature cutting edge research directions addressing both technical and policy issues to advance the state-of-the-art in security techniques, architectures, and algorithms for wireless communications.

The first talk of the series will be delivered by Prof. Vincent Poor, Princeton University.

Date and Time: November 17 at 9AM ET

Registration: Please register using the following link. You will receive a link in your email to attend the talk online.
https://forms.gle/qUoBJtot6yMsCqKX6

Title: Physical Layer Security in Wireless Networks

Abstract: The increasing deployment of wireless systems poses security challenges in emerging dynamic and decentralized networks consisting of very large numbers of low-cost and low-complexity devices. Over the last two decades alternative/complementary means to secure data exchange in wireless settings have been investigated in the framework of physical layer security (PLS), addressing jointly the issues of reliability and secrecy. PLS takes advantage of the inherent randomness of wireless communication channels and/or the unclonability of hardware fabrication processes, to harvest entropy and deliver authentication, confidentiality, message integrity, and privacy in demanding scenarios. In this talk, we review these issues from an information theoretic security perspective. PLS relies on information theoretic proofs of (weak or strong) perfect secrecy, a notion first introduced by Shannon in 1949. As such, PLS systems cannot be “broken” irrespective of the adversarial computational power, i.e., the proofs do not rely on any assumptions regarding the hardness of particular families of algebraic problems. There are some fundamental differences between information theoretic security and classical cryptography, and we will also discuss some of the pros and cons of each.

Bio:  Dr. Vince Poor is the Michael Henry Strater University Professor of Electrical Engineering at Princeton University, where his interests include information theory, machine learning and network science, and their applications in wireless networks, energy systems and related fields.  He is a member of the National Academy of Engineering and the National Academy of Sciences, and a foreign member of the Chinese Academy of Sciences and the Royal Society.  Recognition of his work includes the 2009 ComSoc Edwin Howard Armstrong Award, the 2017 IEEE Alexander Graham Medal, and honorary doctorates from universities in Asia, Europe and North America.

-TCCN SIG on Cognitive Security

Virtual Seminar #4

Dear TCCN fellow members,

Please find our 4th free virtual seminar organised by the IEEE ComSoc TCCN.

Time and date: EDT 9:00am-10:00am (BST 14:00-15:00), Tuesday, 20 October 2020

Venue: online registration via https://www.eventbrite.com/e/symbiotic-radio-achieving-mutualism-spectrum-sharing-using-ris-tickets-123182453033

Title: Symbiotic Radio: Achieving Mutualism Spectrum Sharing using Reconfigurable Intelligent Surfaces

Presenter: Professor Ying-Chang Liang, IEEE Fellow and Editor-in-Chief, IEEE Trans Cognitive Communications and Networking, University of Electronic Science and Technology of China (UESTC), China

Abstract: The heterogeneous wireless services and exponentially growing traffic call for novel spectrum- and energy efficient wireless communication technologies. In this talk, a new technique, called symbiotic radio (SR), is proposed to exploit the benefits of cognitive radio (CR) and reconfigurable intelligent surfaces (RIS), leading to mutualism spectrum sharing and highly reliable backscattering communications. We provide a systematic view for SR which integrates passive radios with active communications, and address its applications in low-power IoT communications in 6G and beyond.

Biography: Ying-Chang Liang is a Professor at University of Electronic Science and Technology of China (UESTC), China, where he leads the Center for Intelligent Networking and Communications (CINC). He was a Professor in University of Sydney, Australia, and a Principal Scientist and Technical Advisor in the Institute for Infocomm Research (I2R), Singapore. His research interest lies in the general area of cognitive radio, dynamic spectrum access, Internet-of-Things, artificial intelligence and machine learning techniques.
Dr Liang was elected a Fellow of the IEEE for contributions to cognitive radio communications, and was also recognized by Thomson Reuters (Now Clarivate Analytics) as a Highly Cited Researcher since 2014. He received the Institute of Engineers Singapore (IES)’s Prestigious Engineering Achievement Award in 2007, and the IEEE Standards Association’s Outstanding Contribution Appreciation Award in 2011. He has also received numerous paper awards, with the recent ones including IEEE ICC Best Paper Awards in 2017 and 2019, IEEE ComSoc’s TAOS Best Paper Award in 2016, and IEEE Jack Neubauer Memorial Award in 2014.
Dr Liang is Founding Editor-in-Chief of IEEE Journal on Selected Areas in Communications-Cognitive Radio Series, and Editor-in-Chief of IEEE Transactions on Cognitive Communications and Networking. He was the Chair of IEEE Communications Society Technical Committee on Cognitive Networks, and served as Guest/Associate Editor of IEEE Transactions on Wireless Communications, IEEE Journal of Selected Areas in Communications, IEEE Signal Processing Magazine, IEEE Transactions on Vehicular Technology, and IEEE Transactions on Signal and Information Processing over Network. He was also an Associate Editor-in-Chief of the World Scientific Journal on Random Matrices: Theory and Applications. Dr Liang was a Distinguished Lecturer of the IEEE Communications Society and the IEEE Vehicular Technology Society, and served as TPC Chair and Executive Co-Chair of IEEE Globecom’17. He will serve as the general chair of IEEE 2018 International Conference on Communication Systems.

Best regards,
Yue Gao
Chair, Technical Committee on Cognitive Networks (TCCN)