Scholar
Yusuke Matsui
Google Scholar ID: kPVJu5UAAAAJ
University of Tokyo
Citations & Impact
Citations
2,585
H-index
19
i10-index
28
Publications
20
Co-authors
35
list available
Contact
Publications
Resume (English only)
Academic Achievements
- November 2025: One paper accepted for TMLR 2025
- October 2025: One paper accepted for SIGGRAPH Asia 2025 Technical Communications
- September 2025: Two papers accepted for NeurIPS 2025 WS
- May 2025: One paper accepted for ICIP 2025
- April 2025: Hosting the 1st Workshop on Vector Databases at ICML 2025
- March 2025: One paper accepted for CVPR 2025
- October 2024: One paper accepted for NeurIPS 2024 WS
- September 2024: Three papers accepted for ECCV 2024 WS
- July 2024: One paper accepted for ACMMM 2024 (Oral)
- April 2024: Papers accepted for ICME 2024 and CVPR WS 2024
- March 2024: Student Yutaro received the Dean's Award; Matsui received the Best Teaching Award from the Faculty of Engineering
- October 2023: Student Hiroki won the Best Paper Award at the AROW Workshop at ICCV 2023
- September 2023: One paper accepted for NeurIPS 2023
- August 2023: Achieved second place in several categories at the SISAP 2023 Indexing Challenge
- August 2023: One paper accepted for ACMMM 2023, another paper accepted for ICCV 2023 WS
- May 2023: Matsui-lab introduced at the Entrance Examination Briefing, accepting master's and doctoral students
- April 2023: Released a website for the AIP acceleration project: High-performance Data Science
- April 2023: Tutorial accepted at CVPR 2023: Neural Search in Action, with Martin and Han
- March 2023: Student Atsuki received the Outstanding Graduation Thesis Award from the Department of Information and Communication Engineering
Research Experience
- Lecturer (Senior Assistant Professor) at the University of Tokyo, leading a research team in the areas of computer vision, data structures, and machine learning.
Education
- Information not provided
Background
- Lecturer (Senior Assistant Professor) at the University of Tokyo, Department of Information and Communication Engineering, focusing on computer vision, data structures, and machine learning. The research group specializes in foundational technologies for large-scale and high-performance AI systems, including vector databases, approximate nearest neighbor search, retrieval-augmented generation (RAG), and learned data structures.
Miscellany
- Personal interests and hobbies not provided
