Yu HouPh.D. Course Student
50 Yonsei-Ro, Seodaemun-Gu |
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I am currently pursuring my Ph.D. at Yonsei University, under the mentorship of Prof. Won-Yong Shin within MIDaS.
My academic journey began with a Master's degree in Applied Mathematics, which I obtained from Ocean University of China (OUC) in Qingdao, in 2021.
My research interests center on graph learning, data analysis, and recommender systems, reflecting my enthusiasm for applying mathematical and computational techniques to understand and solve complex real-world problems. |
I have been exploring the integration of diffusion models with graph learning, aiming to tackle real-world problems, such as recommender systems. Recently, my research has focused on cutting-edge techniques, recommender systems, and LLM-based recommender systems, leveraging LLMs to better capture semantic information and enhance recommendation quality. |
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N/A (double-blind peer review) Yu Hou, Hua Li, Ha Young Kim, Won-Yong Shin. Submitted to the ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD 2025) |
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A Unified Framework for Exploratory Learning-Aided Community Detection Under Topological Uncertainty Yu Hou, Cong Tran, Ming Li, Won-Yong Shin. IEEE Transactions on Network Science and Engineering (TNSE) (SCI) (Accepted) [paper] |
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Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order Connectivity Yu Hou, Jin-Duk Park, Won-Yong Shin. The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Washington DC, USA, 2024. [paper] |
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Robust Mesh Segmentation Using Feature-Aware Region Fusion Lulu Wu, Yu Hou, Junli Xu, Yong Zhao. Sensors, 23 (1): 416, 2023. (SCI) [paper] |
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META-CODE: Community Detection via Exploratory Learning in Topologically Unknown Networks Yu Hou, Cong Tran, Won-Yong Shin. The 31st ACM International Conference on Information and Knowledge Management (CIKM), Atlanta, Georgia, USA, 2022. [paper] |
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3D Mesh Segmentation via L0-constrained Random Walks Yu Hou, Yong Zhao, Xin Shan. Multimedia Tools and Applications, 80 (16), 2021. (SCI) [paper] |
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A Robust Segmentation Algorithm for 3D Complex Meshes Yu Hou, Yong Zhao. The 2020 7th International Conference on Computer-Aided Design, Manufacturing, Modeling and Simulation (CDMMS), Busan, Republic of Korea, 2020. (EI) |
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Application of Deep Learning Method in High Resolution Processing of Significant Wave Height Xiaowen Zhu, Yu Hou, Yuhai Liu, Kejian Wu. Periodical of Ocean University of China, 50 (11), 2020. |
Invited presentation: Yu Hou, Cong Tran, and Won-Yong Shin, "Community Detection Meets Exploratory Learning," presented at the A3 Foresight Program – AI-Based Future IoT Technologies and Services Workshop, Tokyo, Japan, December 2022. |
Invited presentation: Yu Hou, Cong Tran, and Won-Yong Shin, “Overlapping community detection via network exploration,” presented at the Convergence Technology Conference (CTCon), Ho Chi Minh City, Vietnam, December 2022. |
Invited reviewer in WSDM 2023 and WWW 2023. |
Teaching assistant: CSE5023 Fundamentals of Neural Networks and Reinforcement Learning, Spring, 2024-2025. |
Teaching assistant: CSE9981 Fundamentals and Emerging Trends in Graph Learning 2, Spring, 2023-2024. |
Algorithm Research Intern
Topic: Deep Learning for Biodensity Estimation
Algorithm Engineer
Topic: Signal Processing Algorithm Design
National Post-Graduate Mathematical Contest in Modeling, Third Prize Award, 2019. |
Science and Technology Competition Scholarship, Ocean University of China, 2019. |
"Sharing Cup" Innovation Competition of Science and Technology Resources Sharing Service for College Student, Excellence Award, 2020. |
Cultural, Sports and Social Activities Scholarship, Ocean University of China, 2020. |
Excellent Graduate Student, Ocean University of China, 2021. |
Postgraduate Academic Innovation Scholarship, Ocean University of China, 2021. |
International Student Scholarship, Yonsei University, Fall, 2021. |
International Student Scholarship, Yonsei University, Spring, 2022. |
International Student Scholarship, Yonsei University, Fall, 2022. |