Prof. Richard (Chunhui) Yang

Western Sydney University, Australia

Title: TBD

Abstract: TBD

Experience: Prof Richard Yang joined Western Sydney Universityin January 2012 as Associate Professor of Mechanical Engineering and Smart Structures and he was promoted as Professor in 2018. Prior to this, Richard was holding the position of Senior Lecturer in Mechanical Engineering, the School of Engineering, Deakin University (Deakin). He also has worked for acouple of years each in the University of Sydney (USyd) and Korea Advanced Institute of Science and Technology (KAIST) as post-doc research fellow after he finished his PhD in Mechanical Engineering in the University of Hong Kong (HKU) in 2002. He was awarded the Graduate Certificate for Higher Education by Deakin University in 2008.

In research, Prof Yang is an internationally recognised research leader on fields of research include AdvancedManufacturing, Additive Manufacturing (3D printing) of metals, polymers and composites,Advanced Engineering Materials & Structures, Circular Manufacturing & Circular Economy, Defence Technology,Industry 4.0, Machine Condition Monitoring (MCM) & Structural Health Monitoring (SHM), Metal Forming, Metal Surface Treatment, etc.He has been awarded over $12m in competitive research grants, including 12 ARC grants (1 ARC Training Centre, 2 DPs, 3 Linkages, and 6 LIEFs),2 CSIRO/NSF Convergence Accelerator on recycled plastic waste as well as more than 20 from government and/or industry.As for scientific publication,he has published more than 300 high-quality technical publications in top scientific journals, books, and conferences as a major contributor in his relevantfields of research across Mechanical, Mechatronic, Manufacturing, Materials, Aerospace, Civil, Defence, etc.

As for external service, he is serving as assessor for Australian Research Council (ARC), editor board member, conference committee member, reviewerofinternational journals and conferences, examiner for Master and PhD thesis, etc.He is Editor-in-Chief of 2 scientific journals,Associate Editor of 2, and on the Editorial Board of 5. He has been on the ANSHM Executive and the Editor of ANSHM Newsletter since 2016.

Prof. Xiaogang Liu

Wuhan University of Technology, China

Title:TBD

Abstract: TBD

Experience: Prof. Xiaogang Liu acquired his Ph.D. degree in mechanical engineering from the University of Queensland, Australia, and he is now a Professor and Doctoral Supervisor of Mechanical engineering and Instrument Science and Technology at the School of Mechanical and Electrical Engineering, Wuhan University of Technology. He has chaired two scientific research projects supported by the National Natural Science Foundation of China, and his academic outputs include academic papers, invention patents and software copyrights in the fields of Intelligent Manufacturing, Contact Mechanics, Mechanical Vibration and Electromechanical Control. As the leader of a provincial teaching and research project about mechanical manufacturing, he summarised these academic outputs into monographs to integrate research and education, and was recognised as Fellow of Higher Education Academy (FHEA). Currently, he is an assessment expert of the national Natural Science Foundation of China, an assessment expert of China Scholarship Council, a senior member of the Chinese Mechanical Engineering Society, an expert of the high-tech industry in Wuhan, and was awarded the “T A Stewart-Dyer Prize/Frederick Harvey Trevithick Prize” by the Institution of Mechanical Engineers in London.

Prof. Weishan Zhang

China University of Petroleum (East China) , China

Title: TBD

Abstract: TBD

Experience: Professor, Department of Intelligent Science, China University of Petroleum. Qingdao "talent Special Zone" the fourth batch of talents, the West coast New area top talent. Huangdao District "intelligent big data processing innovation talent team" leader, China University of Petroleum "oil big data processing" team leader. Founder and Director of West Coast Artificial Intelligence Technology Innovation Center. Chengyang District, Laoshan District/Chengyang District smart city construction expert, China Communications Society Cloud computing and Big Data committee, China Computer Society pervasive computing committee, Command and Control Society smart wearable technology committee. From 2007 to 2010, he worked as a Research Associate Professor/Senior Researcher at the Department of Computing at the University of Aarhus, Denmark (ranked 63rd in the world in 2009). Since August 2008, he has been the Technical lead of the EU Sixth Framework project Hydra iot Middleware at Aarhus University. From 2006 to 2007, he visited the Department of Systems and Computer Engineering of Carleton University, Canada (Carleton University ranks fifth among all universities in Canada in terms of influence on computers). 2001-2003 Postdoctoral research at the School of Computer Science, National University of Singapore. It has undertaken a number of vertical projects of the Ministry of Science and Technology, the Ministry of Industry and Information Technology, and Shandong Province, as well as a number of horizontal projects of Haier, the Second Aerospace Academy, State Grid, petrochina Exploration Institute, Shengli Oilfield, North China Oilfield, etc. It won the third prize of Qingdao Technology Invention (ranking first), the third prize of Huangdao District Natural Science Award (ranking first), and many other provincial and ministerial awards.

Prof. Liang Hu

Tongji University, China

Title: Federated Learning and Its Promising Applications

Abstract: In recent years, every country has paid increasing attention to data security and personal privacy, which has a direct impact on socioeconomic development. Federated learning is a promising AI method that enables machine learning models to obtain knowledge from different datasets located on different devices or sites without sharing training data. This allows personal data to remain on local devices or sites, reducing the possibility of privacy breaches. 

In this talk, the speaker will introduce the basic concepts of federated learning and the classification of various federated learning approaches. After that, two real applications that demand high-level privacy will be introduced, where the federated learning methods are employed to guarantee the data and personal privacy. Firstly, the speaker will present the federated learning on crowdsourced HD mapping. Secondly, the speaker will present the potential application of federated learning on person re-identification.

Experience: Dr Liang Hu is a full professor with Tongji University and also the Chief AI Scientist with DeepBlue Academy of Science, China. His research interests include recommender systems, machine learning, data science and general intelligence. He has published a number of papers in top-rank international conferences and journals, including WWW, IJCAI, AAAI, ICDM, ICWS, TOIS, IEEE-IS. He has been invited as the program committee of more than 30 top-rank AI international conferences, including AAAI, IJCAI, ICDM, CIKM, and KDD. He also serves as the reviewer of more than ten AI and data science-related international journals, including ACM CSUR, IEEE TKDE, ACM TOIS, IEEE TPAMI, etc. In addition, he has presented eight tutorials on recommender systems and machine learning at top-rank AI conferences including IJCAI, AAAI, SIGIR, and ICDM.