Adjunct Professor
Jasmine Kah Phooi Seng
Faculty of Science,
School of Computer Science
Biography
Dr Jasmine Seng Kah Phooi received her BEng (1st class hons) and PhD degrees from University of Tasmania in Australia. She is currently an Adjunct Professor at School of Computer Science at the Queensland University of Technology (QUT). Dr Seng has worked or attached to Australian-based and UK-based universities including Monash University, Griffith University, University of Tasmania, University of Nottingham, Sunway University, Edith Cowan University and Charles Sturt University. Prior to joining QUT, she was an Adjunct Professor at the University of New South Wales.Her research interests are in computer science and engineering including Artificial Intelligence (AI), data science & machine learning, Big data, multimodal information processing, intelligent systems, Internet of Things (IoT), embedded systems, mobile software development, affective computing, computer vision and the development of innovative technologies for real-world applications. Dr Seng has a strong record of publications and published over 250 papers in journals and international refereed conferences. She has participated over 1.8 million in research grant projects from government and industry in Australia and overseas. She has supervised or co-supervised 12 PhD students to completion and more than 25 higher degree research students. She is an IEEE senior member and associate editor of IEEE Access. She also serves on the editorial board or committees of several journals and international conferences.
Personal details
Positions
- Adjunct Professor
Faculty of Science,
School of Computer Science
Keywords
Artificial Intelligence, Data Science, Big Data, Multimodal Information Processing, Internet of Things (IoT), Embedded Systems
Research field
Artificial intelligence, Electrical engineering
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2020
Qualifications
- PhD in Engineering (University of Tasmania)
- Bachelor of Engineering (1st Class Hons) (University of Tasmania)
Professional memberships and associations
IEEE Senior Member
Publications
- Ang, K. & Seng, J. (2021). Big data and machine learning with hyperspectral information in agriculture. IEEE Access, 9, 36699–36718. https://eprints.qut.edu.au/214210
- Ang, K. & Seng, J. (2021). Embedded Intelligence: Platform Technologies, Device Analytics, and Smart City Applications. IEEE Internet of Things Journal, 8(17), 13165–13182. https://eprints.qut.edu.au/214119
- Ang, K., Ge, F. & Seng, K. (2020). Big Educational Data and Analytics: Survey, Architecture and Challenges. IEEE Access, 8, 116392–116414. https://eprints.qut.edu.au/214211
- Ang, K. & Seng, J. (2019). Application Specific Internet of Things (ASIoTs): Taxonomy, Applications, Use Case and Future Directions. IEEE Access, 7, 56577–56590. https://eprints.qut.edu.au/214214
- Ang, L., Seng, K., Ijemaru, G. & Zungeru, A. (2019). Deployment of IoV for Smart Cities: Applications, Architecture, and Challenges. IEEE Access, 7, 6473–6492. https://eprints.qut.edu.au/214215
- Seng, J. & Ang, K. (2019). Multimodal Emotion and Sentiment Modeling from Unstructured Big Data: Challenges, Architecture, Techniques. IEEE Access, 7, 90982–90998. https://eprints.qut.edu.au/214212
- Seng, K. & Ang, L. (2018). A Big Data Layered Architecture and Functional Units for the Multimedia Internet of Things. IEEE Transactions on Multi-Scale Computing Systems, 4(4), 500–512. https://eprints.qut.edu.au/214134
- Seng, K., Ang, L. & Ooi, C. (2018). A Combined Rule-Based and Machine Learning Audio-Visual Emotion Recognition Approach. IEEE Transactions on Affective Computing, 9(1), 3–13. https://eprints.qut.edu.au/214135
- Seng, K., Ang, L., Schmidtke, L. & Rogiers, S. (2018). Computer vision and machine learning for viticulture technology. IEEE Access, 6, 67494–67510. https://eprints.qut.edu.au/214216
- Seng, J. & Ang, K. (2017). Big Feature Data Analytics: Split and Combine Linear Discriminant Analysis (SC-LDA) for Integration Towards Decision Making Analytics. IEEE Access, 5, 14056–14065. https://eprints.qut.edu.au/214218
QUT ePrints
For more publications by Jasmine Kah Phooi, explore their research in QUT ePrints (our digital repository).