Jun Shen

I am an active researcher and educator in multi-disciplines where computational intelligence applications, cloud and IoT, and data science, as well as general SE/IS methodologies, are applied to solving real life problems. I have been engaged in 40+ funded projects (supported by ARC(DP/LP)/CRC, NSFC, UGPN, DIN, etc) and/or PhD level research topics ranging from AI in education, bioinformatics, intelligent transport, digital health and aged care, to humanistic applications such as arts, human resources, supply chain, media and regional communities. I have also paid many academic visits to top institutions such as MIT, UCI, GaTech, editing journals and chairing academic conferences. I have supervised 26 PhD to in-time completion, all on time, and am supervising another 25 by end of 2024.

I have expertise in two major sub-disciplines: 1. Computational intelligence is applied in many areas for innovative solutions ranging from e-learning, bioinformatics, environmental issues, to transport systems. 2. Cloud and big data applications in many fields such as physics simulation, e-health, energy, aged care, advanced manufacturing and business IS/IT systems.

The top area of my publications and citations falls in bio-inspired algorithmic optimization. Recently I also moved into applying AI in arts, media and communications fields.

I have been leading research centers for applied computing and information systems with AI technologies since 2014 across two different schools, supervising more than 20 early, mid-career researchers. Meanwhile, I am an IEEE Distinguished Lecturer on top of some key editorial positions for top journals such as IEEE Transactions etc. I had won 40+ research grants worth more than 4.5 million Australian dollars.

I have supervised many PhD projects to completion or under way. These include 7 on intelligent transport systems, 7 on services and cloud computing (including edge computing and IoT), 6 on e-learning and open educational resources, 5 on digital health and bioinformatics, 7 on qualitative and quantitative studies on information systems, 4 on sustainable buildings, 4 on agent based system, and a few others on topics such as advanced manufacturing, digital innovation etc.

Contact: solo.shen@gmail.com

Website: https://scholars.uow.edu.au/jun-shen

Linkedin: https://www.linkedin.com/in/jun-shen-37b95337/

Abstracts

Computational intelligence applications in multi-discipline and multi-domains

Abstract: The deep learning is very hot nowadays. However, in many disciplines, the availability of data and the real research questions might not be suitable to apply DL everywhere. In this talk, some generic computational intelligence methods, or their combination with AI/DL based approaches, are explored in applications unto areas such as education, bioinformatics and transportation etc. Hopefully, we can rethink what are key challenges in data science, or, simply data analytic scenarios.

Smart education in the Web 3 era

Abstract: Open educational resources have been talked for many years, but there is controversy how sustainable it could be. Some earlier efforts proposed to develop computational intelligence enabled micro learning, knowledge extraction and other solutions, but they cannot solve the problem of the underlying cost model. This talk introduces a new framework to leveraging some Web 3 economical concepts to build a novel ecosystem supporting future OER development.