Hiromu Taketsugu (武次 広夢)

Hiromu Taketsugu (武次 広夢)

Ph.D. student (M1) at Toyota Technological Institute

Intelligent Information Media Lab.


Hiromu Taketsugu is a Ph.D. student at Toyota Technological Institue, under the supervision of Dr.Norimichi Ukita in Intelligent Information Media Lab. His research interests include artificial intelligence, computer vision, social robotics, and human-robot interaction. He is a member of the Interactive Dynamics (InDy) group, which develops human/scene-interactive and dynamics-aware systems/robots.

  • Artificial Intelligence
  • Computer Vision
  • Social Robotics
  • Human-Robot Interaction
  • M.Eng., 2023-

    Toyota Technological Institute

  • B.Eng., 2019-2023

    Toyota Technological Institute


Computer Vision

I am addicted to creating cutting-edge applications, thinking about future societies and technologies, and understanding how human intelligence works through computer vision.

Machine Learning

I was a TA for a year in a well-known machine learning course attended by more than 1,000 people each semester.


I like to devise ways to increase my productivity and I actively try out new tools.


I develop mainly on Linux, e.g. Ubuntu.


I got a minor in mechanical engineering as an undergraduate, but I am still learning.

Dogs and cats

I have one friendly Maltese and one lovely Ragdoll-Siamese mix.

Social Community

Set up vista, a community for mutual progress management, with my best friend in 2020 and still running it.


Books that rethink everyday life in a scientific way or give me time for philosophical speculation.


I love learning languages, travelling to new places and connecting with new people. I am learning English, Chinese and Vietnamese (my wife is Vietnamese).


Exercise is a good companion that energises me and boosts my productivity. I was captain of the Spartan Race Club in my university.

Recent Publications

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(2023). Uncertainty Criteria in Active Transfer Learning for Efficient Video-Specific Human Pose Estimation. 2023 18th International Conference on Machine Vision and Applications (MVA).


(2023). 効率的な動画別の人体姿勢推定を目的とした能動転移学習の不確実性基準. 情報処理学会研究報告(Web).

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