Xuan-May Le
Ph.D. Student at The University of Melbourne
About Me
Research Interest: Machine Learning, Time Series Data Mining, Computer Vision and AI for Healthcare
I am currently a Ph.D. student at the School of Computing and Information Systems, the University of Melbourne. I am very fortunate to be advised by Prof. Uwe Aickelin and Dr. Ling Luo. I received my Master of Knowledge Science from JAIST, Japan, and my Bachelor in Computer Science from Ton Duc Thang University.
Contact Details
Email: xuanmay.le(at)student.unimelb.edu.au / xuanmay (at) outlook.com
Website: Google Scholar
Github: https://github.com/xuanmay2701
EDUCATION
The University of Melbourne, Australia
Doctoral Student in Computer Science (August 2023 - Now)
Japan Advanced Institute of Science & Technology (JAIST), Ishikawa, Japan
Research and Master Student in Computer Science (Sep. 2020 - June 2023)
PUBLICATION
Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, Dinh Phung.
Text-Enhanced Data-free Approach for Federated Class-Incremental Learning.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, 2024. (top tier conference)
Source code is available here.Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, Quan Hung Tran, Dinh Phung.
NAYER: Noisy Layer Data Generation for Efficient and Effective Data-free Knowledge Distillation.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA, 2024. (top tier conference)
Source code is available here.Xuan-May Le, Minh-Tuan Tran, Van-Nam Huynh.
Learning Perceptual Position-aware Shapelets for Time series Classification.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Grenoble, France, 2022. (top tier conference)
Source code is available here.Xuan-May Le, Minh-Tuan Tran, Hien T Nguyen.
An Improvement of SAX Representation for Time Series by Using Complexity Invariance.
Intelligent Data Analysis (IDA), 2020. (IF: 1.70).Minh-Tuan Tran*, Xuan-May Le*, Hien T Nguyen, Van-Nam Huynh.
A Novel Non-Parametric Method for Time Series Classification Based on k-Nearest Neighbors and Dynamic Time Warping Barycenter Averaging.
Engineering Applications of Artificial Intelligence (EAAI), 2019. (IF: 8.00)Thuc‑Doan Do, Minh‑Tuan Tran, Xuan‑May Le, Thuy‑Van Duong.
Detecting Special Lecturers Using Information theory‑ based Outlier Detection Method.
Proceedings of the International Conference on Compute and Data Analysis (CCDA), 2017.Minh-Tuan Tran*, Xuan-May Le*, Vo Thanh Vinh, Hien T Nguyen, Tuan .M Nguyen.
A Weighted Local Mean-based k-Nearest Neighbors Classifier for Time Series.
International Conference on Machine Learning and Computing (ICMLC), Singapore, 2017.
AWARDS & HONORS
2023 Melbourne Research Scholarship, The University of Melbourne
2023 Dean’s Award, JAIST
2021‑2023 Japanese Government (MEXT) Scholarship for Master Students, JAIST
2020‑2021 Japanese Government (MEXT) Scholarship for Research Students, JAIST