Keynote Speakers

Prof. Sajal K. Das

Affiliation

Daniel St. Clair Endowed Chair
Department of Computer Science
Missouri University of Science and Technology

Title

Securing Cyber-Physical and IoT Systems in Smart Living Environments

Abstract

Our daily lives are increasingly dependent on a variety of smart cyber-physical infrastructures, such as smart cities and buildings, smart energy grid, smart transportation, smart healthcare, etc. Alongside, smartphones and sensor-based IoTs are empowering humans with fine-grained information and opinion collection through crowdsensing about events of interest, resulting in actionable inferences and decisions. This synergy has led to the cyber-physical-social (CPS) convergence with human in the loop, the goal of which is to improve the “quality” of life. However, CPS and IoT systems are extremely vulnerable to failures, attacks and security threats. This talk will highlight unique research challenges in securing such systems, followed by novel defense mechanisms. Our proposed frameworks and solutions are based on a rich set of theoretical and practical design principles, such as secure data fusion, uncertainty reasoning, information theory, prospect theory, reputation scoring, and belief and trust models. Two case studies will be considered: (1) Security forensics and lightweight statistical anomaly detection in the smart grid CPS to defend against organized and persistent adversaries that can launch data falsification attacks on the smart meters using stealthy strategies. The novelty of our approach lies in a newly defined information-theoretic metric that helps quantify robustness and security, thus minimizing the attacker’s impact on the customers and utilities with low false alarm rates; (2) Secure and trustworthy decision making in mobile crowd sensing to detect false (or spam) contributions due to selfish and malicious behavior of users. Based on the cumulative prospect theory and reputation/trust model, our approach prevents revenue loss owing to undue incentives and improves the operational reliability and decision accuracy. The talk will be concluded with directions for future research.

Short Bio

Dr. Sajal K. Das is a Professor of Computer Science and Daniel St. Clair Endowed Chair at the Missouri University of Science and Technology, where he was the Chair of Computer Science Department during 2013-2017. He also served the NSF as a Program Director in the Division of Computer Networks and Systems (CNS) under the CISE directorate during 2008-2011. Prior to 2013, Dr. Das was a University Distinguished Scholar Professor of Computer Science and Engineering and founding director of the Center for Research in Wireless Mobility and Networking (CReWMaN) at the University of Texas at Arlington. In 2012, the Science Foundation of Ireland selected him as the E.T.S. Walton Fellow. Dr. Das has been a visiting professor at University of Pisa, Italy; Cork Institute of Technology, Ireland; Indian Institute of Technology, Kanpur; Fudan University, Beijing Jiaotong University, and Zhejiang Gongshang University, China.

Dr. Das’ research interests include wireless and sensor networks, mobile and pervasive computing, cyber-physical systems and smart environments (such as smart healthcare and smart grid), cyber security, IoT, big data analytics, distributed and cloud computing, biological and social networks, applied graph theory and game theory. He has directed over $15M funded research projects and published more than 700 research papers in high quality journals and refereed conference proceedings. He holds 5 US patents, co-authored 51 invited book chapters, and four books on Smart Environments: Technology, Protocols, and Applications (John Wiley, 2005), Handbook on Securing Cyber-Physical Critical Infrastructure: Foundations and Challenges (Morgan Kauffman, 2012), Mobile Agents in Distributed Computing and Networking (Wiley, 2012), and Principles of Cyber-Physical Systems: An Interdisciplinary Approach (Cambridge University Press, 2018). According to DBLP, Dr. Das is one of the most prolific authors in computer science. His h-index is 79 with more than 26,000 citations according to Google Scholar. He has graduated 41 Ph.D. students.

Dr. Das is a recipient of 10 Best Paper Awards at prestigious conferences, such as ACM MobiCom, IEEE PerCom, and IEEE SmartGridComm. He is also a recipient of numerous awards for research, teaching, mentoring and professional services, including the IEEE Computer Society’s Technical Achievement Award for pioneering contributions to sensor networks and mobile computing, and IEEE Region-5 Outstanding Educator Award. Dr. Das serves as the founding Editor-in-Chief of Elsevier’s Pervasive and Mobile Computing journal (since 2005), and serves as Associate Editor of several journals including IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. A (co-) founder of IEEE PerCom, IEEE WoWMoM, IEEE SMARTCOMP, and ICDCN conferences, he has served as General Chair, Technical Program Chair, and Program Committee member of numerous ACM and IEEE conferences. Dr. Das is an IEEE Fellow.

 
Prof. Jiannong Cao

Affiliation

Department of Computing

Hong Kong Polytechnic University

Title

EdgeMesh: Enabling Scalable Connectivity and Distributed Intelligence for IoT

Abstract

In the past decade, applications of Internet of Things (IoT) such as Smart Home, Smart Cities, Smart Healthcare etc. have been deployed where the devices in our surroundings are interconnected to provide better services and comfort to humans. More recently, we witness the emerging applications in industrial internet, supply chains and other areas where the scale of the systems, the number of devices and data being generated continuously increases. It will be at very high cost to send all the data to a centralized server, as done in cloud computing, for processing and decision-making. Therefore, recent trend is to move the computation tasks from centralized cloud to edge devices which are closer to data sources. In this talk, I describe a new infrastructure for IoT named Edge Mesh, where the intelligence and decision-making are pushed to the edge of and within the network closer to the sources of data by letting the edge devices share the data and collaborate on the computation tasks. EdgeMesh also facilitates higher scalability and reliability with flexible and dynamic system reconfiguration.

Short Bio

Dr. Cao is currently a Chair Professor of Department of Computing at The Hong Kong Polytechnic University, Hong Kong. He is also the director of the Internet and Mobile Computing Lab in the department and the director of University’s Research Facility in Big Data Analytics. His research interests include parallel and distributed computing, wireless sensing and networks, pervasive and mobile computing, and big data and cloud computing. He has co-authored 5 books, co-edited 9 books, and published over 600 papers in major international journals and conference proceedings. He received Best Paper Awards from conferences including IEEE DSAA 2017, IEEE SMARTCOMP 2016, IEEE ISPA 2013, IEEE WCNC 2011, etc. Dr. Cao served the Chair of the Technical Committee on Distributed Processing of IEEE Computer Society from 2012 to 2014, a member of IEEE Fellows Evaluation Committee of the Computer Society and the Reliability Society, a member of IEEE Computer Society Education Awards Selection Committee, a member of IEEE Communications Society Awards Committee, and a member of Steering Committee of IEEE Transactions on Mobile Computing. He has also served as chairs and members of organizing and technical committees of many international conferences, and as associate editor and member of the editorial boards of many international journals. Dr. Cao is a fellow of IEEE and ACM distinguished member. In 2017, he received the Overseas Outstanding Contribution Award from China Computer Federation.

 
Prof. Daqing Zhang

Affiliation

Peking University

Title

Towards Millimeter-scale Human Activity Sensing with Wi-Fi Signals: Theory and Applications

Abstract

In this talk, Prof.Zhang will introduce the Fresnel zone model as a new theoretic basis for non-intrusive human sensing with Wi-Fi signals. The theory not only reveals why human body movement produces wavelength-scale fluctuation in the received RF signal, but also sheds light on the sensing limit of Wi-Fi devices. Building on the Fresnel Zone Model and the frequency diversity of WiFi signals, millimeter-scale human activity sensing could be achieved. Prof.Zhang will use human respiration detection as an application example to demonstrate the power of the proposed theory.

Short Bio

Daqing Zhang is a Chair Professor at the School of EECS, Peking University, China and Vice Chair of CCF Pervasive Computing Technical Committee. His research interests include context-aware computing, mobile computing, big data analytics and pervasive elderly care. Dr. Zhang has published more than 200 technical papers in leading conferences and journals, where his work on context model is widely accepted by the pervasive computing, mobile computing and service-oriented computing communities. He served as the general or program chair for more than 10 international conferences, giving keynote talks at more than 20 international conferences. He is the associate editor for ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Big Data, IEEE Pervasive Computing, etc.. In recent years, he has been exploring new areas such as 'Social and Community Intelligence (SCI)', 'Mobile Crowd Sensing (MCS)' and 'Contactless Sensing' which aim to push context-aware computing to new frontiers. Dr. Zhang is the winner of the Ten-years CoMoRea impact paper award at IEEE PerCom 2013, the Honorable Mention Award at ACM UbiComp 2016 and 2015, the Best Paper award at IEEE UIC 2015 and 2012, and the Best Paper Runner Up award at Mobiquitous 2017 and 2011. Daqing Zhang obtained his Ph.D. from University of Rome “La Sapienza' in 1996.

 
Prof. Hai Jin

Affiliation

Huazhong University of Science and Technology

Title

Architecture Consideration for Big Data Processing

Abstract

With emerging of big data, the processing speed for the data is one of the key issues for big data technology. One of the efficient way to handle the velocity of data is putting all the data in the memory. But traditional memory, DRAM, consumes a large amount of energy and cost to build a large memory system. In recent years, lots of non-volatile memory devices, such as phase change memory (PCM), are studied to be part of memory. We call these storage class memory (SCM). Combing traditional memory and SCM together to build a large hybrid memory space is becoming one of the energy-efficient way to extend the traditional in-memory computing system into a new level, to handle large quality of data in real time. In this talk, we will discuss this new in-memory computing system from different aspects and some challenges in this new system. We will also report some ongoing effort in China to build this hybrid memory-based in-memory computing system, and some latest advances in this area.

Short Bio

Hai Jin is a Cheung Kung Scholars Chair Professor of computer science and engineering at Huazhong University of Science and Technology (HUST) in China. Jin received his PhD in computer engineering from HUST in 1994. In 1996, he was awarded a German Academic Exchange Service fellowship to visit the Technical University of Chemnitz in Germany. Jin worked at The University of Hong Kong between 1998 and 2000, and as a visiting scholar at the University of Southern California between 1999 and 2000. He was awarded Excellent Youth Award from the National Science Foundation of China in 2001. Jin is the chief scientist of ChinaGrid, the largest grid computing project in China, and the chief scientists of two National 973 Basic Research Program Project of Virtualization Technology of Computing System, and Cloud Security.

Jin is a Fellow of CCF, senior member of the IEEE and a member of the ACM. He has co-authored 22 books and published over 800 research papers. His research interests include computer architecture, virtualization technology, cluster computing and cloud computing, peer-to-peer computing, network storage, and network security.

 
Prof. Minyi Guo

Affiliation

Shanghai Jiao Tong University

Title

Towards the new platform for Urban Big data processing

Abstract

Nowadays, sensing technologies and large-scale computing infrastructures have produced a variety of big data in urban spaces, e.g. human mobility, air quality, traffic patterns, and geographical data. The big data implies rich knowledge about a city and can help tackle these challenges when used correctly. That is, holistic urban big data plays the key role in smart city constructions. However, processing urban big data needs the specific computing engine different with traditional one such as Hadoop and Spark, because the sensing and knowledge representation are more complicated than domain-specific big data. In this talk, we will give some properties for processing urban big data and introduce a new platform for processing and analyzing urban big data. Then we discuss how the collaborative computing bridges the data and computation in the cyber space and the environment, systems, people and things in the physical world.

Short Bio

Minyi Guo received the BSc and ME degrees in computer science from Nanjing University, China; and the PhD degree in computer science from the University of Tsukuba, Japan. He is currently Zhiyuan Chair professor and head of the Department of Computer Science and Engineering, Shanghai Jiao Tong University (SJTU), China. Before joined SJTU, Dr. Guo had been a professor of the school of computer science and engineering, University of Aizu, Japan. Dr. Guo received the national science fund for distinguished young scholars from NSFC in 2007, and was supported by “Recruitment program of Global Experts” in 2010. His present research interests include parallel/distributed computing, compiler optimizations, embedded systems, pervasive computing, big data and cloud computing. He has more than 400 publications in major journals and international conferences in these areas. He received 5 best paper awards from international conferences. He is now on the editorial board of IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing and Journal of Parallel and Distributed Computing. Dr. Guo is a fellow of IEEE, and a fellow of CCF.

 
Prof. Yong Lian

Affiliation

National University of Singapore

Short Bio

Dr. Lian Yong received the B.Sc. degree from the College of Economics and Management, Shanghai Jiao Tong University, Shanghai, China, in 1984, and the Ph.D. degree from the Department of Electrical Engineering, National University of Singapore (NUS), Singapore, in 1994. He worked in industry for nine years and joined NUS in 1996, where he served as the Deputy Department Chair for Research, Area Director for IC and Embedded Systems in the ECE Department, member of University Tenure and Promotion Committee, and member of Senate Delegacy. He was appointed as the first Provost’s Chair Professor in the Department of Electrical and Computer Engineering of NUS in 2011. He is a member of National Thousand Talents Program and a Chair Professor in the School of Microelectronics. Dr. Lian is a Fellow of Academy of Engineering Singapore and a Fellow of IEEE.

Dr. Lian’s research interests include biomedical circuits and systems and signal processing. He has received many awards including IEEE Circuits and Systems Society’s Guillemin-Cauer Award (1996), IEEE Communications Society Multimedia Communications Best Paper Award (2008), Institution of Engineers Singapore Prestigious Engineering Achievement Award (2011), Hua Yuan Association/Tan Kah Kee International Society Outstanding Contribution Award (2013), Chen-Ning Franklin Yang Award in Science and Technology for New Immigrant (2014), and Design Contest Award in 20th International Symposium on Low Power Electronics and Design (ISLPED2015).

Dr. Lian is the President of the IEEE Circuits and Systems (CAS) Society, Member of IEEE Fellow Committee, Steering Committee Member of the IEEE Transactions on Biomedical Circuits and Systems. He was the Editor-in-Chief of the IEEE Transactions on Circuits and Systems Part II: Express Briefs. He was the Guest Editor for eight special issues in IEEE Transactions on Circuits and Systems-Part I: Regular Papers, IEEE Transactions on Biomedical Circuits and Systems, and Journal of Circuits, Systems Signal Processing. He was the Vice President for Publications of the IEEE CAS Society, Vice President for the Asia Pacific Region of the IEEE CAS Society, Member of the IEEE Medal for Innovations in Healthcare Technology Committee, and a Distinguished Lecturer of the IEEE CAS Society. He is the Founder of the International Conference on Green Circuits and Systems, the Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics, and the IEEE Biomedical Circuits and Systems Conference.