Guanjin (Brenda) Wang  from Murdoch University in Perth Australia.
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Phone

9360 7351

Email

Guanjin.Wang@murdoch.edu.au

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    Dr Guanjin (Brenda) Wang
    PhD (PolyU, UTS), MIT and BITS

    Lecturer in Information Technology

    About me

    Guanjin (Brenda) Wang is a lecturer in the Discipline of Information Technology, Mathematics and Statistics in the College of Science, Health, Engineering and Education. Prior to joining Murdoch University in November 2018, she obtained a joint Ph.D. degree from The Hong Kong Polytechnic University (PolyU) and University of Technology Sydney (UTS). It was a wonderful journey in which she became well prepared for being an independent researcher with a continuous interest in a variety of research topics. Her current research focuses on artificial intelligence, machine learning, data mining, and health informatics.

    Teaching area

    • ICT583 Data Science Applications
    • ICT602 Advanced Data Analysis
    Previous Teaching Units:
    • BSC301 Applied Research Skills in ICT
    • ICT521 IT Professional Practice
    I also coordinate off-shore units at Murdoch Dubai and Singapore campuses.
    I am also the second academic chair of Masters of IT.

    Research areas

    AI and Machine Learning

    Data Mining

    Transfer Learning

    Health Informatics

    Professional and community service

    IEEE Member, ACS Member, Fellow of HEA

    Vice Chairperson in IEEE Western Australia Section – SMC Chapter committee  (2019-current)

    Treasurer in IEEE Western Australia Section – CIS/RAS Chapter committee (2018-current)

    Doctoral and masters supervisions

    PhD students (co-supervising):

    Bimal Philip Weerakody

    Lixia Ma

    Publications

    Journals

    • Wang, G., Zhang, G., Choi, K., Lam, K., Lu, J., (2020), Output based transfer learning with least squares support vector machine and its application in bladder cancer prognosis, Neurocomputing: an international journal, 387, 28 April 2020, .
    • Wang, G., Teoh, J., Lu, J., Choi, K., (2020), Least squares support vector machines with fast leave-one-out AUC optimization on imbalanced prostate cancer data, International Journal of Machine Learning and Cybernetics, Published 27 Feb 2020, , .

    https://scholar.google.com/citations?user=rqn08ogAAAAJ&hl=en