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2023 6th International Conference on Computing and Big Data(ICCBD 2023)

Keynote Speakers 主旨报告

ICCBD 2022 Keynote Speakers



Prof. Min Chen

 Huazhong University of Science and Technology, China


Min Chen is a full professor in School of Computer Science and Technology at Huazhong University of Science and Technology (HUST) since Feb. 2012. He is the director of Embedded and Pervasive Computing Lab, and the director of Data Engineering Institute at HUST. He is the founding Chair of IEEE Computer Society Special Technical Communities on Big Data. He was an assistant professor in School of Computer Science and Engineering at Seoul National University before he joined HUST. He is the Chair of IEEE Globecom 2022 eHealth Symposium. His Google Scholar Citations reached 34,150+ with an h-index of 89. His top paper was cited 3,800+ times. He was selected as Highly Cited Researcher from 2018 to 2021. He got IEEE Communications Society Fred W. Ellersick Prize in 2017, and the IEEE Jack Neubauer Memorial Award in 2019. He is an IEEE Fellow for his contributions to data-driven communication, caching, and computing.

Title: Near-human Sensing in Fabric Smart Space

Abstract: In future network, the provisioning of ultra-low latency, non-intrusive and immersive service experience creates various challenges, among which near-human sensing is of great importance to obtain multi-modal information without disturbing user. This talk introduces the development of various functional fabrics, which have provided new thoughts for generating novel near-human services interconnected by fabric sensors, body area network, edge cloud and visualization system. In order to embrace digital intelligent world, this talk also presents the fabric smart space empowered by intelligent fabric agents, which gather multidimensional sensory data and interactive information via near-human sensing technologies. Finally, several examples with the use of fabric smart space are given in terms of sport, healthcare and medical scenarios.



Prof. Liu Chi

 Beijing Institute of Technology, China

IET, Fellow of British Computer Society and Chinese Institute of Electronics Fellow

Prof. Chi (Harold) Liu receives a Ph.D. degree in Electronic Engineering from Imperial College, UK in 2010, and a B.Eng. degree in Electronic and Information Engineering from Tsinghua University, China in 2006.
He is currently a Full Professor and Vice Dean at the School of Computer Science and Technology, Beijing Institute of Technology, China. Before moving to academia, he worked for IBM Research - China as a staff researcher and project manager from 2010 to 2013, worked as a postdoctoral researcher at Deutsche Telekom Laboratories, Germany in 2010, and as a Research Staff Member at IBM T. J. Watson Research Center, USA in 2009. His current research interests include the big data analytics, mobile computing, and machine learning. He received the IBM First Plateau Invention Achievement Award in 2012, ACM SigKDD'21 Best Paper Runner-up Award, ACM MobiCom'21 Best Community Paper Runner-up Award, and IEEE DataCom'16 Best Paper Award. He has published more than 100 prestigious conference and journal papers and owned 37 EU/UK/US/Germany/Spain/China patents. He serves as the Associate Editor for IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, Area Editor for KSII Trans. on Internet and Information Systems, the Symposium Chair for IEEE ICC 2020 on Next Generation Networking, and served as the (Lead) Guest Editor for IEEE Transactions on Emerging Topics in Computing and IEEE Sensors Journal. He was the book editor for 11 books published by Taylor \& Francis Group, USA and China Machine Press, China. He also has served as the general chair of IEEE SECON'13 workshop on IoT Networking and Control, IEEE WCNC'12 workshop on IoT Enabling Technologies, and ACM UbiComp'11 Workshop on Networking and Object Memories for IoT. He was a consultant to Asian Development Bank, Bain & Company, and KPMG, USA, and the peer reviewer for Qatar National Research Foundation, National Science Foundation, China, Ministry of Education and Ministry of Science and Technology, China. He is a senior member of IEEE and a Fellow of IET, British Computer Society, and Royal Society of Arts.

Title: Energy-Efficient 3D Vehicular Crowdsourcing for Disaster Response by Distributed Deep Reinforcement Learning

Abstract: Fast and efficient access to environmental and life data is key to the successful disaster response. Vehicular crowdsourcing (VC) by a group of unmanned vehicles (UVs) like drones and unmanned ground vehicles to collect these data from Point-of-Interests (PoIs) e.g., possible survivor spots and fire site, provides an efficient way to assist disaster rescue. In this paper, we explicitly consider to navigate a group of UVs in a 3-dimensional (3D) disaster work zone to maximize the amount of collected data, geographical fairness, energy efficiency, while minimizing data dropout due to limited transmission rate. We propose DRL-DisasterVC(3D), a distributed deep reinforcement learning framework, with a repetitive experience replay (RER) to improve learning efficiency, and a clipped target network to increase learning stability. We also use a 3D convolutional neural network (3D CNN) with multi-head-relational attention (MHRA) for spatial modeling, and add auxiliary pixel control (PC) for spatial exploration. We designed a novel disaster response simulator, called “DisasterSim”, and conduct extensive experiments to show that DRL-DisasterVC(3D) outperforms all five baselines in terms of energy efficiency when varying the numbers of UVs, PoIs and SNR threshold.


Prof. Chen Chun-Hsien

Nanyang Technological University, Singapore

Chun-Hsien CHEN is Full Professor, Director of the Design Stream, and Professor-in-Charge of the Design & Human Factors Lab in the School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore. He received his BS degree in Industrial Design from National Cheng Kung University, MS and Ph.D. degrees in Industrial Engineering from the University of Missouri-Columbia, USA. He has several years of product design & development experience in the industry. His teaching and research interests are design science in product design and development; engineering/design informatics for managing/ supporting digital design & manufacturing; and human factors and management of human performance. He has more than 270 publications in these areas. Prof. Chen has served as a Technical Reviewer for National Science and Technology Awards (Singapore), National Research Foundation of Korea, The Knowledge Foundation (KK) HÖG 16 Project, Sweden, and a Judge for Pin Up Design Awards (South Korea), an Advisory Board member for ISTE (International Society of Transdisciplinary Engineering), an Advisory Committee member for the various international conferences held in USA, Europe, Brazil, China, Korea, Malaysia, Hong Kong and Taiwan. Prof. Chen has been appointed as Editor-in-Chief of Advanced Engineering Informatics (ADVEI) since January 2013 and Associate Editor of Space Mission Planning & Operations (SMPO) since August 2022. Besides, he is/was an editorial board member of Journal of Engineering Design, Recent Patents on Engineering, Journal of Kansei, Heliyon, etc. He is/was a Shanghai Eastern Scholar (2011 – 2014), a Guest Professor of Tianjin University (since 2013), a Visiting Professor of National Cheng Kung University (2011), a Guest Professor of Shanghai Maritime University (since 2006), and Chaoyang University of Technology (2008 – 2010).

Title: Human-Centric Smart Product-Service Systems and Beyond

Abstract: Technology, consumer sophistication and business globalization have led to a highly competitive business environment which demands faster new product (tangible or intangible) introduction and more complex and value-added, customized products. Since the primary role of product design is to bridge users and technological systems in contexts of product use, it is increasingly important to focus on human-centric concerns, such as understanding the users’ behaviour, needs and requirements of different social and cultural segments. As these human-centric factors become more important in product design and development along with increasing complexity from technological advances such as networking and embedded technologies, multi-disciplinary information management becomes critical for achieving high product integrity. Yet, because of the complexity, uncertainty and cross-disciplinary nature of human and societal factors, formal mechanisms for incorporating these factors consistently into the product design and development process have not been well established. In this regard, Smart Product-Service System (Smart PSS) is emerging as an IT-driven value cocreation business strategy by integrating smart, connected products and its generated digitalized and e-services into a single solution to meet individual customer needs in a sustainable manner, especially important in the era of Industry 4.0 and beyond.

Keywords: Human-centric design, smart product-service systems, design informatics, digital twin

Prof. Weidong Li

University of Shanghai for Science and Technology, China

Proessor Weidong Li is the dean of the mechanical engineering school at University of Shanghai for Science and Technology. He obtained his PhD degree in mechanical engineering from National University of Singapore in 2002. He worked for Singapore Institute of Manufacturing Technology, Bath University, Cranfield University and Coventry University (become a full professor in 2013). His research areas are smart manufacturing and sustainable manufacturing enabled by big data analytics. In the areas, he has led over 20 major R&D projects sponsored by European Commission, EPSRC (UK), Innovate UK (UK), NSFC (China) and industries like Airbus, Jaguar Land Rover, Sandvik, to name a few. He published five books (Springer) and over 200 research papers in the international journals and conferences. He received two “industrial success story” awards from European Commission, two “best paper” awards from two international journals, and four “best paper” awards from international conferences in the UK, USA, Portugal and China. He is an associate editor for five international journals.

Title: Data Driven Smart Manufacturing and Industrial Cases


Prof. Yongsheng Ma

Southern University of Science and Technology, China

Dr. Yongsheng Ma has been a full professor at Southern University of Science and Engineering in Shenzhen, China since July, 2021. Before that he had been a full professor at University of Alberta where he had joined since 2007. Dr. Ma is also a member of ASME, ASEE, SME, SPE, CSME and an Alberta registered Professional Engineer (P.Eng.). His main research areas include engineering informatics for design and manufacturing, CADCAM, and product lifecycle management. Dr. Ma received his B.Eng. from Tsinghua University, Beijing (1986), both M.Sc. (1990) and Ph.D. (1994) from UMIST, UK. In 2000-2007, he was an associate professor with Nanyang Technological University, Singapore. Dr. Ma started career as a Ngee Ann Polytechnic lecturer in Singapore (1993); and then a senior research fellow and group manager (1996-2000) at Singapore Institute of Manufacturing Technology. Dr. Ma has published more than 200 internationally recognized top journal and conference papers, and two specialty books. Dr. Ma had been an associate editor of IEEE Transaction of Automation Science and Engineering (2009-2013). In 2012, he won the prestigious ASTech award sponsored by The Alberta Science and Technology Leadership Foundation together with Drader Manufacturing Ltd. Dr. Ma had been engaged for collaboration with many academic institutions and industrial partners internationally. 2019-2020, Dr. Ma had been a visiting professor of SUSTech. Since 2020, Dr. Ma has become an associate editor for Advanced Engineering Informatics (Elsevier), ASME Journal of Computer Information Science and Engineering (JCISE), and Frontiers in Mechanical Engineering – Digital Manufacturing (Frontiers, open access). He also serves as an Editorial Member for Scientific Reports published by Springer Nature.

Title:  Smart Product Development and the Application Trends in Industry

Abstract: This presentation is about the new trends of smart product development and applications in the context of industrial integration within supply chains, from an angle of engineering informatics. Smart product application development, represented by a framework of multi-scale smart devices connected with collaborative network-based resources is becoming an essential business strategy in critical global markets. Keeping the industrial competitiveness depends on the integration technologies over the big-data intelligence, algorithms, and especially the cyber-physical systems. This scenario can be only supported by deep-collaboration in an ever more integrated and yet highly ambiguous and customized environment. Critical review of integrative technologies in engineering informatics field is to be presented. The contents mainly focus on data associativity and deep interoperability among smart product applications. Hopefully, the proposed collaborative data integration approach will generate meaningful discussion about new challenges, strategies and technical systematic solutions focusing on interoperability, robustness, and optimized resources collaboration.

Keywords: Network-oriented engineering management; Industry 4.0; Smart Product Engineering; Deep-Collaboration, Real-time Data Integration and Reasoning; Value-chain