Tien-En Chang (張天恩)
Tien-En Chang (張天恩)
Institue of Industrial Engineering, National Taiwan University
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I am Tien-En (Willy), a PhD candidate at National Taiwan University (NTU) in Taipei, Taiwan, and a member of the Statistical and Data Mining Lab under the supervision of Prof. Argon Chen.
My primary research interests lie in variable selection and interpretable statistical methodology. My research began with relative importance analysis, where I investigated why Johnson’s Relative Weight performs remarkably well in approximating the General Dominance Index, also known in this context as the Shapley Value. Building on this line of work, I currently focus on improving Relative Weight methods by strengthening their theoretical foundations and exploring possible methodological refinements.
More broadly, I am interested in understanding the behaviors of statistical and machine learning methods.
Recent News
Recent News
Mar. 2026: Our paper, "Variable Selection Using Relative Importance Rankings", has been accepted for publication in Pattern Recognition [paper].
Jan. 2026: Our paper, "Understanding and Using the Relative Importance Measures Based on Orthogonalization and Reallocation", has been accepted for publication in Statistical Science [paper].
Sep. 2025: Our work, “Anatomically-Focused Patches for Lightweight and Explainable Knee OA Grading,” received the Best Paper Award in MICCAI ShapeMI 2025 [paper].
Aug. 2025: One workshop paper accepted to ShapeMI 2025 in MICCAI 2025! See you at Daejeon!
Feb. 2025-Jun. 2025: Joined 2025 Polytechnique Montreal Winter Research Internship Program.
Research topic: Machine Learning and Interaction with Large-Scale Medical Imaging Datasets. Under the supervition of Prof. Herve Lombaert in the PolyShape Lab. Internship Program Report: 蒙特婁理工學院實習心得
May. 2024: One abstract accepted to DATA 2024! See you at Dijon!
Tien-En Chang, Argon Chen. Understanding the Orthonormality Transformation based Measures of Relative Importance.
Nov. 2023: Celebrating our team's success: Awarded the Outstanding Award at the Intelligent Manufacturing and Big Data Analytics Contest 2023.
The finals of Project B: the image classification problem in the manufacturing. Team name: 真替你們感到難過; members: Huai-Wei Wang, Zih-An Yi, Tien-En Chang; mentor: Jakey Blue
Oct. 2023: One abstract accepted to IASC-ARS 2023! See you at Sydney!
Tien-En Chang, Argon Chen. Using Relative Weight for Variable Importance Assessment - How Does It Work and Could It Work Better?
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