Atsuyuki Miyai 宮井 淳行

I'm Atsuyuki Miyai. Now, I'm a 1st-year PhD student of the Yamasaki Lab at The University of Tokyo.

Before that, I received Master degree under the supervision of Prof. Kiyoharu Aizawa at UTokyo. With his retirement approaching, I have moved to the Yamasaki Lab, but I will continue collaborative research with the Aizawa Lab and tackle with the same research topic.

My research collaborators are Dr. Qing Yu (LY Corporation) and Prof. Go Irie (Tokyo Univ. of Science).

My research focuses on the safety of large pre-trained neural networks. In particular, I put an emphasis on defining new problems and aim to provide a simple, baseline approach to give insights.

Email  /  Twitter  /  Github  /  Google Scholar

The University of Tokyo
Ph.D. in Graduate School of Information Science and Technology
Supervisor: Prof. Toshihiko Yamasaki
2024.4 -

The University of Tokyo
M.S. in Graduate School of Interdisciplinary Information Studies
Supervisor: Prof. Kiyoharu Aizawa
2022.4 - 2024.3

The University of Tokyo
B.S. in Under Graduate School of Engineering
Information and Communication Engineering
Supervisor: Prof. Kiyoharu Aizawa
2018.4 - 2022.3

2024.4: 🎉 Our new preprint, Unsolvable Problem Detection, has been out in arXiv!

2024.4: Doctoral program begins at the University of Tokyo.

2024.3: 🎉 Our new work (preliminary version) has been accepted by ICLR 2024 R2-FM Workshop! Stay tuned for the details.

International

2024

• Unsolvable Problem Detection: Evaluating Trustworthiness of Vision Language Models
  Atsuyuki Miyai, Jingkang Yang, Jingyang Zhang, Yifei Ming,
  Qing Yu, Go Irie, Yixuan Li, Hai Li, Ziwei Liu, and Kiyoharu Aizawa
  arXiv, 2024
  ICLR Workshop on Reliable and Responsible Foundation Models, 2024 (preliminary version)
  paper  /  code

• Can Pre-trained Networks Detect Familiar Out-of-Distribution Data?
  Atsuyuki Miyai, Qing Yu, Go Irie, and Kiyoharu Aizawa
  arXiv, 2023
  paper  /  code (comming soon)




• LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning
  Atsuyuki Miyai, Qing Yu, Go Irie, and Kiyoharu Aizawa
  Neural Information Processing Systems (NeurIPS), 2023
  paper  /  code




• Zero-Shot In-Distribution Detection in Multi-Object Settings Using Vision-Language Foundation Models
  Atsuyuki Miyai, Qing Yu, Go Irie, and Kiyoharu Aizawa
  arXiv, 2023
  paper  /  code



• Rethinking Rotation in Self-Supervised Contrastive Learning:
  Adaptive Positive or Negative Data Augmentation
  Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie, and Kiyoharu Aizawa
  Winter Conference on Applications of Computer Vision (WACV), 2023
  paper  /  code

• CLIPを用いたゼロショット分布内検知
  宮井 淳行, 郁 青, 入江 豪, 相澤 清晴
  IE, 2024, IE Award
  
  
• CLIP-based In-distribution Detection
  Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa
  MIRU, 2023 (short oral)
  
  
• Rethinking Rotation for Contrastive Learning: Adaptive Positive or Negative Data Augmentation
  Atsuyuki Miyai, Qing Yu, Daiki Ikami, Go Irie, Kiyoharu Aizawa
  MIRU, 2022 (long oral), Best Student Paper
  
  
• 自己教師あり学習のための適応的正負例データ拡張
  宮井 淳行, 郁 青, 伊神大貴, 入江 豪, 相澤 清晴
  IPSJ (情報処理学会), 2022, Student Encouragement Award
  

2024.3: The Dean's Award, The Best Master Thesis Award

2024.2: IE Award @IE (画像工学研究会) Feb. 2024

2023.7: Interactive Presentation Award @MIRU 2023

2022.7: Best Student Paper Award @MIRU 2022
Awarded The Best Student Paper Award by The Association for Meeting on Image Recognition and Understanding (Japanese representative scientific and professional society for researchers working on problems involving computer vision).
Please refer to the official homepage.

2022.3: Student Encouragement Award @Information Processing Society of Japan (IPSJ) 2022

2023.6 ~ 2023.12: OMRON SINICX
Research Internship.   Mentor: Dr. Yoshitaka Ushiku, Dr. Atsushi Hashimoto, Dr. Kuniaki Saito

2022.8 ~ 2022.9: Preferred Networks
Research Internship.   Mentor: Dr. Masanori Koyama, Dr. Kohei Hayashi, Dr. Yuta Kikuchi, Dr. Yoshihiro Yamada

2020.10 ~ 2023.03: Pluszero Inc.
Project Engineer.  I tackle natural language processing.

2023.12 ~ : OpenOOD
Research activities.   Collaborators (≒Mentors): Jingkang Yang (Nanyang Technological University), Jingyang Zhang (Duke University), Yifei Ming (University of Wisconsin-Madison)

2023.4 ~ : IEEE Student Branch Chair @UTokyo
We have a diverse range of workshops, invited talks, and hands-on activities focused on advancing knowledge and skills in a particular field or topic. Please feel free to contact us when you visit Tokyo!
Please refer to the official homepage.