Profile picture of Jie-En (Matthew) Yao

Jie-En Yao

I am a Ph.D. student in Computer Science at the University of Southern California, advised by Prof. C.-C. Jay Kuo. My research focuses on computer vision and machine learning, with interests in representation learning, visual understanding, and generative modeling. Previously, I received my Bachelor's degree in Computer Science from National Tsing Hua University, advised by Prof. Chun-Yi Lee.
Publications

HCL-FF: Hierarchical and Contrastive Learning for Forward-Forward Algorithm

Jie-En Yao, Hong-En Chen, C-C Jay Kuo

CVPR 2026, IEEE/CVF Conference on Computer Vision and Pattern Recognition

Descrip3D: Enhancing Large Language Model-based 3D Scene Understanding with Object-Level Text Descriptions

Jintang Xue, Ganning Zhao, Jie-En Yao, Hong-En Chen, Yue Hu, Meida Chen, Suya You, C-C Jay Kuo

WACV 2026, IEEE/CVF Winter Conference on Applications of Computer Vision

SHFE: Transparent And Green Image Classification Via Supervised Hierarchical Feature Extraction

Jie-En Yao, Xinyu Wang, C-C Jay Kuo

ICIPW 2025, IEEE International Conference on Image Processing Workshops

Ma-Yolo: Video Object Detection Via Motion-Assisted Yolo

Xinyu Wang, Hong-Shuo Chen, Zhiruo Zhou, Jie-En Yao, C-C Jay Kuo

ICIPW 2025, IEEE International Conference on Image Processing Workshops

Local Implicit Normalizing Flow for Arbitrary Scale Image Super-Resolution

Jie-En Yao, Li-Yuan Tsao, Yi-Chen Lo, Roy Tseng, Chia-Che Chang, Chun-Yi Lee

CVPR 2023, IEEE/CVF Conference on Computer Vision and Pattern Recognition

ELDA: Using Edges to Have an Edge on Semantic Segmentation Based UDA

Ting-Hsuan Liao, Huang-Ru Liao, Shan-Ya Yang, Jie-En Yao, Li-Yuan Tsao, Hsu-Shen Liu, Bo-Wun Cheng, Chen-Hao Chao, Chia-Che Chang, Yi-Chen Lo, Chun-Yi Lee

BMVC 2022, British Machine Vision Conference

Experience
AI Research InternHsinchu, Taiwan
  • Prototyped, optimized, and iterated on advanced deep learning architectures, efficiently translating research ideas into high-quality experimental results
  • Developed a novel arbitrary-scale super-resolution model, achieving state-of-the-art performance and publication at CVPR
Data Science InternHsinchu, Taiwan
  • Performed data preprocessing, feature engineering, and trained predictive Machine Learning models to forecast production quality, enabling data-driven quality control
Teaching
  • Data Science Professional Practicum @ USC (Graduate Course)

    Spring 2026, with Prof. Young Cho
    • Hosted weekly office hours and provided guidance on student projects
  • Principles of Programming for Data Science @ USC (Graduate Course)

    Fall 2025, with Prof. Alexey Tregubov
    • Led weekly lab sessions and office hours, supporting 50+ students develop Python and data science foundations
  • Introduction to Programming @ NTHU (Undergraduate Course)

    Spring 2021, with Prof. Po-Chih Kuo
    • Hosted weekly TA session to help students develop their C++ programming proficiency
Service
Reviewer: CVPR, NeurIPS, WACV, IEEE Transactions on Image Processing, ACM Transactions on Multimedia Computing, Communications, and Applications, Journal of Visual Communication and Image Representation, APSIPA Transactions on Signal and Information Processing
Miscellaneous

Outside of work, I’m a big sports fan, particularly basketball and soccer. I also like playing poker, especially for the strategy behind it. In the winter, I like to hit the slopes and go skiing. I'm powered by coffee and Coca-Cola.

Fun fact: I absolutely love orcas (which is why one happens to be the logo of this website).