Minh-Tuan Tran

EDUCATION

Monash University, Melbourne,  Australia
Ph.D in Artificial Intelligence (March 2023 - Now)

Korea Advanced Institute of Science & Technology (KAIST), Daejeon, Korea
M.S in Computer Science (Sep. 2020 - Sep 2022)

Ton Duc Thang University, Ho Chi Minh City, Vietnam
B.S in Computer Science (Sep. 2013 - Sep. 2017)

PUBLICATION

Preprints:

1. Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, Jianfei Cai, Dinh Phung.
   Large-Scale Data-Free Knowledge Distillation for ImageNet via Multi-Resolution Data Generation
   Source code is available here.

PhD Process:

1. Minh-Tuan Tran, Trung Le, Xuan-May Le, Thanh-Toan Do, Dinh Phung.
   Enhancing Dataset Distillation via Non-Critical Region Refinement.
   CVPR 2025,  Nashville, USA.  (CORE A*)
   Source code is available here.

2. Xuan-May Le, Ling Luo,  Uwe Aickelin, Minh-Tuan Tran, David Berlowitz, Mark Howard
   SHIP: A Shapelet-based Approach for Interpretable Patient-Ventilator Asynchrony Detection
   PAKDD 2025, Sydney, Australia  (CORE A)

3. Minh-Tuan Tran, Trung Le, Xuan-May Le, Mehrtash Harandi, Dinh Phung.
   Text-Enhanced Data-free Approach for Federated Class-Incremental Learning.
   CVPR 2024, Seattle, USA. (CORE A*)
   Source code is available here.

4. 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.
   CVPR 2024, Seattle, USA. (CORE A*)
   Source code is available here.

5. Minh-Tuan Tran, Xuan-May Le, Van-Nam Huynh, Sung-Eui Yoon.
   PISD: A linear complexity distance beats dynamic time warping on time series classification and clustering.
   Engineering Applications of Artificial Intelligence (EAAI), 2024. (IF: 7.50)
   Source code is available here.

6. Xuan-May Le, Ling Luo, Uwe Aickelin, Minh-Tuan Tran.
   ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification.
   KDD 2024, Barcelona, Spain (CORE A*)
   Source code is available here.

Pre-PhD:

7. Xuan-May Le*, Minh-Tuan Tran*, Van-Nam Huynh.
   Learning Perceptual Position-aware Shapelets for Time series Classification.
   ECML PKDD 2022,  Grenoble, France. (CORE A)
   Source code is available here.

8. 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).

9. 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: 7.50)

10. 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.
    ICMLC 2017, Singapore.

11. Thuc‑Doan Do, Minh‑Tuan Tran, Xuan‑May Le, Thuy‑Van Duong.
    Detecting Special Lecturers Using Information theory‑ based Outlier Detection Method.
    ICCDA 2017, USA. 

AWARDS & HONORS

1. Monash International Tuition Scholarship (MITS) , Monash, 2023-Now

2. Research Training Program Scholarship (RTP), Monash, 2023-Now

3. International Graduate Student Scholarship, KAIST, 2020-2022

4. Top 20 Outstanding Students in Ton Duc Thang University, 2016-2017 

5. NAFOSTED  Grant Program for Research Support Activities 2017

ACADEMIC EXPERIENCE

Monash University's Tutor: FIT9136 - Algorithms and programming foundations in Python, 2025-S1.

Paper Reviewer:  ICLR 2024, ICML 2025, ICCV 2025, NeurIPS 2025