Shunsuke Kitada, Ph.D.

Shunsuke Kitada, Ph.D.

Research Scientist working on Vision & Language with Deep Learning

Research Scientist @ Image and Video AI Dept., LY Corp.

Kioi Tower 1-3 Kioicho, Chiyoda-ku, Tokyo, 102-8282, Japan

Project Researcher @ Hosei University

S603, 3-7-2, Kajino-cho, Koganei-shi, Tokyo 184-8584, Japan

Intelligent information processing laboratory


Shunsuke Kitada (北田 俊輔 in Japanese) is a Research Scientist at Image and Video AI Dept., LY Corp. His research interest is now on computational advertising with a focus on automatic geneartion/evaluation and assistive technology for multi-modal ad creatives.

Previously, he got his Ph.D. in 2023 at major in applied informatics, graduate school of science and engineering, Hosei University under the supervision of Prof. Hitoshi Iyatomi. His project was to improve prediction performance and model interpretability through attention mechanisms from basic and applied research perspectives.

His personality traits can be summarized as follows:

  • ❤️ Love research and development. He is enjoying research life, and he is currently focusing on three research topics simultaneously, e.g., natural language processing, medical image-based computer vision, computational advertising.
  • 📝 Every day read and implement the SoTA models. He has released many re-implementations of models using mainly Chainer and PyTorch. Therefore, based on state-of-the-art cases, he can advise on deep learning-based product design.
  • 😄 High technical communicativity. Summarize what he made and what he studied, and spread such information. This shows that he can input and output regularly.

The resume is available in PDF .

Background image borrowed from OpenAI ChatGPT illustration by Ruby Chen.

  • 🤖 Natural Language Processing
  • 💻 Computer Vision
  • 🏥 Medical Image Processing
  • 📃 Computational Advertising
  • PhD in Engineering, 2023

    Graduate School of Science and Engineering, Hosei University

  • MSc in Engineering, 2020

    Graduate School of Science and Engineering, Hosei University

  • BSc in Engineering, 2018

    Hosei University

📝 Conference Paper (Refereed)

All Conference Papers »

🇯🇵 Domestic Conference / Presentation in Japan

All domestic conference »

🎙️ Recent & Upcoming Talks

All recent and upcoming talks »

👨‍💻 Selected Experiences

All experiences can be found on my LinkedIn.

Research Scientist
October 2023 – Present Kioi Tower 1-3 Kioicho, Chiyoda-ku, Tokyo, 102-8282, Japan
Transferred due to merge between LINE Corp. and Yahoo! Japan Corp.
Research Scientist
April 2023 – September 2023 Yotsuya Tower 23rd FL., 1-6-1 Yotsuya, Shinjuku-ku, Tokyo, 160-0004, Japan
June 2023 – June 2026 Teheran-ro, Gangnam-gu, Seoul, Korea
  • Taught lectures on image-generating AI at Coloso, an online education service
  • The lectures can be found at the following URL:
Teaching Assistant / Mentor
January 2016 – April 2021
Fundamental Information Technology Engineer
June 2016 – Present
Fundamental Information Technology Engineer Examination is a yardstick for measuring IT knowledge and skills as a team member by asking a range of questions about algorithm, network, database, information security, practical programming, etc.

📂 Projects


AllenNLP Eraser

Collection of AllenNLP DatasetReaders for ERASER

Paper Survey

Paper Survey

📚Survey of previous research and related works on machine learning (especially Deep Learning) in Japanese.

Hosei University Soft Tennis Club Hp

Hosei University Soft Tennis Club Hp

🎾 Hosei University Soft Tennis Club’s home page repository.


Implementation of Focal loss in Chainer.


Implementation of RICAP in Chainer.


Implementation of LSUV (Layer-sequential unit-variance) in PyTorch.


High-speed Deep learning API Server with Libtorch (C++) and Gin (Golang)


A tool for enriching the output of nvidia-smi forked from peci1/nvidia-htop.


Implementation of PyramidNet in Chainer.


Implementation of InceptionResNetV2 in Chainer.


Implementation of IMSAT in Chainer.


Implementation of Center Loss in Chainer.