Dr Khanh Luong
Faculty of Science,
Tier 1 Research Centre - Science (U91),
Centre for Data Science
Biography
Dr. Khanh Luong finished her PhD in Computer Science specializing in Data Science from Queensland University of Technology in 2019. She is working as a Postdoctoral Researcher in Data Science at QUT Centre for Data Science. Her research is concerned with dealing multiple aspect data, one of emerging, promising and challenging research topics in recent years. The multiple aspect data that is represented by multiple views and contain different types of multiple relationship has become commonly available along with the advancements in technology, yet very high-dimensional and extreme sparse. The practice of having more informative data requires the learning method to be able to exploit, as much as possible, all the available data in order to capture the true valuable hidden knowledge from data and return informative outcomes. Her research has contributed to the fields of machine learning and data mining by developing various innovative methods ready to be deployed on real-world datasets ranging from text, image, sound, video and bioinformatics data, in diverse problems such as clustering, classification, anomaly detection, community discovery or collaborative filtering with the novel multi-aspect outlook. Currently, she is working on the Applied Data Science project, one of core projects of QUT Centre for Data Science, which aims to produce effective solutions dealing with complex datasets, ranging from text data to sensor data, generated from real-world industry problems.Personal details
Positions
- Adjunct Lecturer
Faculty of Science,
Tier 1 Research Centre - Science (U91),
Centre for Data Science
Qualifications
- Doctor of Philosophy (Queensland University of Technology)
Teaching
Since 2017, Dr. Khanh Luong has tutored several units at QUT for both undergraduate and postgraduate including,
- Discrete mathematics
- Programming Principles
- Database Management
- Programming Fundamentals (for Master of IT students)
- Introduction to Programming (for Master of IT students)
- Object Oriented Programming (for Master of IT students)
- Project 1 (for Master of IT students)
- Project 2 (for Master of IT students)
She has also been a course designer for the online unit Introduction to Programming (IFQ555) for Master of IT students.
Experience
Research Areas /Problems
- Data Mining, Machine Learning
- Multi-Aspect Image and Text Mining (Clustering, Community Detection)
- Dimensionality Reduction and Manifold Learning
- Unsupervised, Semi-supervised, Transfer Learning
- Data Fusion
Professional Activity
- Organizing Committee Member (Organizing Chair):
- The 2021 Australasian Data Mining Conference (AusDM)
- PC member:
- The AusDM 2021 conference
- The AusDM 2020 conference
- Reviewer:
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- IEEE Transactions on Neural Networks and Learning Systems (T-NNLS)
Publications
QUT ePrints
For more publications by Khanh, explore their research in QUT ePrints (our digital repository).