Prof. George G.Q. Huang is Chair Professor and Head of Department in Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong. He gained his BEng and PhD in Mechanical Engineering from Southeast University (China) and Cardiff University (UK) respectively. He has conducted research projects in the field of Physical Internet (Internet of Things) for Manufacturing and Logistics with substantial government and industrial grants. He has published extensively including over two hundred refereed journal papers in addition to over 200 conference papers and ten monographs, edited reference books and conference proceedings. His research works have been widely cited in the relevant field. He serves as associate editors and editorial members for several international journals. He is a Chartered Engineer (CEng), a fellow of ASME, HKIE, IET and CILT, and member of IIE.
Prof. George G.Q. Huang has been serving on editorial boards of a number of international journals. He is Editor for Asia Pacific for International Journal of Computer Integrated Manufacturing, Associate Editor of International Journal of Production Research, Area Editor for Business & Management for International Journal of Research in Engineering Design, and Associate Editor for Journal of Intelligent Manufacturing.
Prof. George G.Q. Huang received 2014 First-Class Guangdong Province (Department of Science and Technology) on "Mass-Customized Design and Production System", 2007 First-Class Natural Science Award from Chinese Ministry of Education on "Service-oriented manufacturing execution in extended enterprises", 2007 Outstanding Young Researcher Award (Overseas) from Natural Science Foundation of China and 2001 The University of Hong Kong Outstanding Young Researcher Award.
Keynote Speaker I I
Virtual reality is the technology that can make people immerse into a virtual environment as in a real world. The virtual environment replicates a real or imagined environment, and simulates a user’s physical presence and interactive environment. The immersive environment can be similar to the real world, in order to create a lifelike experience, or it can significantly differ from reality world, such as in virtual reality magic games. The most outstanding feature of virtual reality is immersive. Cutting off the connection between your perception with the virtual world can pull you out of the threat from the virtual environment. It can be described like this, virtual reality makes player’s perception immerse in the virtual environment meanwhile the body is physically in the real world. In reality, human has five senses. The five senses can make human percept different attributes of the world, and bridge the connection between human with the environment. Virtual realities artificially create sensory experience, that can include sight, touch, hearing, and smell. During the senses, the sight is the most important. Some advanced haptic systems now include tactile information. The tactile information is generally known as force feedback. Moreover, virtual reality covers remote communication environments which provide virtual presence of users with the concepts of telepresence and telecommunication either through the use of standard input devices such as a keyboard and mouse, or through multimodal devices such as a digital glove or omnidirectional treadmills. My research is mainly on exploring the combination of Virtual Reality and the emerging technologies, such as Blockchain, Internet of Things, Deep Learning. For example, the combination of Virtual Reality and Internet of Things is Digital Twins, the combination of Virtual Reality and Blockchain is Blocknetwork.
Dr. Zhihan Lv, ACM Distinguished Speaker, IEEE Senior Member and British Computer Society Fellow. He received joint PhD. degree from Ocean University of China and the University of Paris. He has served as a research engineer at the French National Research Center in France, a postdoctoral fellow at Umeå University in Sweden, a experienced researcher at the FIVAN Foundation in Spain, a postdoctoral fellow at University College London in UK, a postdoctor at the University of Barcelona in Spain, and an research assistant professor at the Chinese Academy of Sciences. He was a Marie Curie Fellow in European Union's Seventh Framework Program LANPERCEPT. He has published more than 270 high-quality papers in virtual reality, Internet of Things, big data and other fields, in which 43 papers were published in the top journal IEEE/ACM Transactions.
Research in recent years has been published in IEEE TII, IEEE TITS, IEEE TFS, IEEE TSMC, IEEE TETC, IEEE TBD, IEEE JSAC, IEEE JSTSP, IEEE IOTJ, IEEE COMMAG, IEEE Network, ACM TOMM, ACM TOIT, ACM TIST, and conferences such as ACM MM, ACM CHI, ACM Siggraph Asia, ICCV, IEEE Virtual Reality. Published more than ten highly cited papers and one hot paper.
He won the "Best idea" award in the UMINOVA academic business competition in Sweden, the grand prize in the "Challenge Cup" entrepreneurial plan competition in China, the "Chunhui Cup" award in the innovation and entrepreneurship competition for Chinese overseas students, the third prize in the China "Challenge Cup" extracurricular academic technology competition, the third prize of Shandong Province Graduate Student Outstanding Scientific and Technological Innovation Achievement Award, the third prize of Shandong Province Higher Education Institution Humanities and Social Science Outstanding Achievement Award, and the 2020 Qingdao University Outstanding Graduate Supervisor Award.
Dr. Zhihan Lv served as editorial board member of journals, including Plos one, IEEE Access, IET Image Processing, KSII Transactions on Internet and Information Systems, and Neurocomputing. Served as the Lead Guest Editor of several well-known journals, including IEEE Transactions on Industrial Informatics, IEEE Network, IEEE Transactions on Intelligent Transportation Systems, IEEE Sensors, IEEE Consumer Electronics Magazine, IEEE Communications Standards Magazine, IEEE Journal of Biomedical and Health Informatics, Future Generation Computer Systems, Neurocomputing and Applications, Neurocomputing, etc., organized more than 40 special issues. Served as the vice chair and TPC members of ACM IUI 2015-2021, IEEE INFOCOM 2020 workshop, ACM MobiCom 2020 workshop, IEEE VTC2017-Fall, IEEE CHASE Workshop 2016, 2017, IEEE/CIC WIN Workshop 2016, ISAIR2021. In 2018, he won the IEEE Access Outstanding Associate Editor Award.
Dr. Zhihan Lv has reviewed more than 260 manuscripts for high-level journals and conferences, including IEEE TMM, ACM TOMM, IEEE TII, IEEE TBD, IEEE TMC, IEEE TLT, IEEE TETC, IEEE TC, IEEE TVCG, IEEE TITS, IEEE/ACM TCBB, ACM TOIT, IEEE Network, IEEE MultiMedia, IEEE IOTJ and other journals and ACM MUM, ACM CHI, ACM DIS, IEEE EuroVis, ACM UIST, ACM MobileHCI, ACM CHIPLAY, ACM CSCW, ACM SUI, ACM ITS, IEEE VAST, IEEE VR, ACM IUI, IEEE 3DUI, ACM TVX, ACM Creativity & Cognition, ACM EICS, ACM IDC, IEEE ICSIPA, GI, IEEE ITSC, IEEE Sensors, ACM ACI, ACM VRST, ACM ISS, ACM HRI and other conferences. He is the reviewer of the Swiss National Natural Science Foundation.
Deep Learning is a subset of Artificial Intelligence, which directs computing to perform classification tasks directly from texts, images, or signals. Deep Learning is one of the most popular domains in the AI space, allowing to develop multi-layered models of varying complexities. The term deep refers to the number of hidden layers in the network. For optimal results, Deep Learning requires large amounts of data and substantial computing power.
In this talk, we will see the foundations of Deep Learning, we understand how to build an advanced deep neural network and learn how to lead successful machine learning. Most methods of Deep Learning are on neural network architectures especially the optimization techniques.
The swarm intelligence as an optimization technique can achieve a complex and intelligent behavior through the local interactions between its members. The algorithms of swarm intelligence are integrated to deep learning to optimize the corresponded parameters.
Optimized Deep Learning has its applications in the fields of Automated Driving, Image Recognition, Emotion and Fraud Detection, Natural Language Processing, Healthcare, Security, Personalized Services, and more.
Boudour Ammar is currently an assistant professor with the Department of
Computer Engineering and Applied Mathematics at National Engineering School of
Sfax (ENIS). She was born in Sfax, Tunisia. She graduated in computer science in
2005. She received the Master degree in automatic and industrial computing from
the National School of Engineers of Sfax, University of Sfax in 2006. She
obtained a PhD degree in recurrent neural network learning model for a biped
walking simulator with the Research Group on Intelligent Machines (REGIM),
University of Sfax, since February 2014.
Her research interests include iBrain (Artificial neural networks, Machine learning, Recurrent neural Network) & i-health (Autonomous Robots, Intelligent Control, medical applications, EEG and ECG signals).
In recent years, Dr. Boudour published many highly cited research papers in IEEE
Transaction of neural Networks and Learning systems, IEEE Transactions on
Affective Computing, Neural Processing Letters, Applied Soft Computing,
Neurocomputing, Cybernetics and systems journals. She also published papers in
conferences such as International Joint Conference on Neural Networks (IJCNN),
International Conference on Neural Information Processing, IEEE International
Conference on Systems, Man, and Cybernetics.
She, currently, serves as a reviewer of some international conferences and journals like Neural Computing and IEEE TNNLS.
She also served in several volunteering positions as a head of the Career Center and Certification Skills 4C-ENIS, IEEE WIE Tunisia Affinity Group chair, chair and Vice-chair of IEEE Computational Intelligence Societies & IEEE RAS Tunisia and YP active Member. She organized the Robocomp robotics competition and the World Robot Olympiad Tunisia Qualification. She served as an organizing member in several workshops and international conferences including Workshop on Intelligent machines Theory & Applications (WIMTA), Workshop in Intelligent Decision Support Systems (iDSS), Multi-Conference on Systems, Signals and Devices (SSD).