Brief portfolio

I am a Ph.D. candidate in Computer Science at the National Taiwan University of Science and Technology. My expertise includes deep learning, computer vision, small language models (SLMs), and large language models (LLMs), with strong proficiency in Microsoft Azure and multi-agent systems for impactful AI solutions.

I am actively seeking opportunities in Generative AI and Computer Vision, open to roles in Taiwan or remotely. Connect with me on LinkedIn to explore potential collaborations or opportunities.

Medium

Language

• Chinese: Native
• English: TOEIC 845
• Japanese: JLPT N2

Education

Sep 2020 – Expected Graduation: Aug. 2024
國立臺灣科技大學-資工所。
Ph.D. Candidate, Department of Computer Science at National Taiwan University of Science and Technology，Taiwan Tech
Research field: Generative AI, Computer Vision based on Deep learning.
Multimedia and Visual Computing Laboratory advised by Prof. Kai-lung Hua.

Sep 2019 – Mar 2020
RWTH Aachen University, Germany
Exchange Student, Faculty of Electrical Engineering and Information Technology.

Feb 2018 – Mar 2020
國立臺灣科技大學-資工所。
Master degree in Computer Science at National Taiwan University of Science and Technology，Taiwan Tech
Research field: Computer Vision based on Deep learning.
Published 2 journals and 2 conference papers, including 1 IEEE Transaction, and 1 oral paper in the best IEEE image processing conference(ICIP).
Master’s thesis: Adapting Semantic Segmentation of Urban Scenes via Mask-aware Gated Discriminator.
The 13th Best Master Thesis Award of Chinese Image Processing and Pattern Recognition Society(IPPR).

Sep 2014 – Jan 2018
國立臺灣科技大學，主修資工系。
Bachelor in Computer Science at National Taiwan University of Science and Technology，Taiwan Tech
Early Graduation based on Academic Excellence, GPA - 3.91/4.0 (Ranked 3rd out of 53).
Academic Excellence Award, Awarded to top 5% students in class each semester.

Publication

• Kuan-Hung Huang, Yao-Bang Huang, Yong-Xiang Lin, Kai-Lung Hua, Mohammad Tanveer, Xuequan Lu, Imran Razzak. “GRA: Graph Representation Alignment for Semi-Supervised Action Recognition,” to appear in IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024. (Impact Factor 2022: 10.451).
• Yao-Bang Huang, Yong-Xiang Lin, Ahmad Fauzan Aqil, Yung-Yao Chen, Kai-Lung Hua. “Graph Involutional Networks with Dynamic Feature Fusion for Skeleton-Based Action Recognition.” In Proceedings of the 2024 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA, Jan. 5-8, 2024.
• Balin Lin, Yong-Xiang Lin, Bayisa Kune Mamade, Yung-Yao Chen, Kai-Lung Hua. “GazeVAE: Gaze Visual Attention Estimator.” In Proceedings of the 2024 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA, Jan. 5-8, 2024.(Best Poster Paper Award)
• Jilyan Dy, John Jethro Virtusio, Daniel Tan, Yong-Xiang Lin, Joel Ilao, Yung-Yao Chen, Kai-Lung Hua. “MCGAN: Mask Controlled Generative Adversarial Network for Image Retargeting,” Neural Computing and Applications (NCAA), vol. 35, pp. 1-13, Feb. 2023. (Impact Factor 2021: 5.102).
• Yong-Xiang Lin, Daniel Stanley Tan, Yung-Yao Chen, Ching-Chun Huang, and Kai-Lung Hua. “Domain Adaptation with Foreground/Background Cues and Gated Discriminators,”IEEE MultiMedia Magazine, vol. 27, no. 3, pp. 44-53, Jul-Sep. 2020. (Impact Factor 2019: 4.962).
• Daniel Stanley Tan, Yong-Xiang Lin, and Kai-Lung Hua. “Incremental Learning of Multi-Domain Image-to-Image Translations,” to appear in IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT). (Impact Factor 2019: 4.133).
• Yu-Cheng Liu, Mohammad Shahid, Wannaporn Sarapugdi, Yong-Xiang Lin, Jyh-Cheng Chen, Kai-Lung Hua, Cascaded Atrous Dual Attention U-Net for Tumor Segmentation, Multimedia Tools and Applications (MTAP). (Impact Factor 2019: 2.313).
• Yong-Xiang Lin, Daniel Tan, Wen-Huang Cheng, Yung-Yao Chen, and Kai-Lung Hua. “Spatially-aware Domain Adaptation for Semantic Segmentation.” In Proceedings of the IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, Sep. 22 - 25, 2019.
• Yong-Xiang Lin, Daniel Stanley Tan, Wen-Huang Cheng, Kai-Lung Hua. “Adapting Semantic Segmentation of Urban Scenes via Mask-aware Gated Discriminator,” In Proceedings of the IEEE International Conference on Multimedia & Expo (ICME), Shanghai, China, Jul. 8 - 12, 2019.

Awards

• 2024, 42th Best Poster Award by the International Conference on Consumer Electronics (ICCE)
• 2020, 中華民國影像處理與圖形識別學會(IPPR)第十三屆博碩士論文獎碩士論文優等獎 論文題目：基於遮罩門控鑑別器之自適應城市場景語意分割模型
• 2013, 金手獎 102年度全國高中職工科技藝競賽-電腦軟體設計工 金手獎第三名