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  9. arrow_forward_ios Jie Lu: Distinguished Professor, Laureate Fellow, FEIT

Jie Lu: Distinguished Professor, Laureate Fellow, FEIT

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About my work

Jie Lu: Distinguished Professor, Laureate Fellow, FEIT

My advances have had a major impact on my research communities, and for the evolution of Australian society and our 21st-century economy. I was one of the earliest scholars to integrate fuzzy systems into machine learning; in particular I pioneered fuzzy transfer learning, which transfers knowledge learnt in source domains to a target domain, in which labelled data is insufficient for learning. In a substantial body of work reported in more than 20 IEEE Transactions papers, her team initiated and developed fuzzy transfer learning methods and algorithms, for example, by building fuzzy latent feature space that can bridge domains; this solved very challenging uncertainty issues in transfer learning from multiple angles. I led the invention of an evolving type-2 fuzzy classifier that can start its learning process from scratch with an empty rule base – where fuzzy rules can be automatically grown, pruned, recalled, and merged in real time (which earnt an IEEE Outstanding Paper Award).

A memorable win

In 2019, I gained a prestigious Australian Laureate Fellowship – a first at UTS. The ARC’s Laureate scheme supports the best Australian researchers in their pursuit of highly significant research goals as they build Australia’s research capacity – with a strong emphasis on developing and mentoring the next generation of researchers, preparing them for careers that will make a difference in Australian industry and universities. My Laureate project is creating an integrated and holistic computational foundation for a new research direction – autonomous learning-based decision-making – enabling effective, autonomous machine learning from big data to support decision-making in complex (massive, uncertain, dynamic) situations.

Bio: Distinguished Professor Jie Lu is an internationally renowned scientist in the area of Artificial Intelligence. She has made fundamental and influential contributions, particularly in fuzzy transfer learning, concept drift, data-driven decision support systems, and recommender systems. Professor Lu has applied her expertise and theoretical innovations across a wide range of industry sectors, including transportation, telecommunications, and healthcare. Her achievements have been recognised by 10 international and Australian research awards.

An IEEE Fellow, IFSA Fellow, and Australian Laureate Fellow, Professor Lu has published six books and more than 450 papers in leading journals and conference proceedings, with 16,500 citations and an H-index of 67. She has delivered 30 keynote speeches at international conferences, and has been Editor-in-chief for Knowledge-Based Systems (KBS, Elsevier) since 2009. She set up strategies and flagships, leading 24 associate editors (including 30-40% females). Under her editorial leadership the Impact Factor increased from 0.9 in 2009 to 8.0 in 2021; now ranked 16/140 in the CS & AI category. 

Professor Lu is also editor-in-chief of Int J Computational Intelligent Systems (Springer) (since 2011). Editor-in-Chief, Intelligent Information Systems book series (World Scientific), since 2007. Leadership for Women-in-STEM: Keynote/Invited speaker for many activities related to Australian women in research, e.g., in 'Women in Research Webinar' (2021) and 'Early Career Women Writing Workshop' (2020).  

At UTS, Professor Lu is the Director of the Australian Artificial Intelligence Institute – the largest AI centre in Australia, with 40 researchers and 230 PhD students; she has supervised 50 PhD students to completion. As the Associate Dean (Research Excellence) of the Faculty of Engineering and IT, she has driven the Faculty’s culture of research excellence. She has secured 10 ARC Discovery projects and an ARC Linkage project, and has led 15 industry projects. 

Websites

UTS profile page: https://profiles.uts.edu.au/Jie.Lu

Acknowledgement of Country

UTS acknowledges the Gadigal People of the Eora Nation and the Boorooberongal People of the Dharug Nation upon whose ancestral lands our campuses now stand. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands. 

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