Shoki Miyagawa

2025.07- Graduate School of Management, GLOBIS University
2023.02- Preferred Networks Product  Owner / Engineering Manager
2019.04-2023.01 Mitsubishi Electronic Researcher
2019.03 Waseda University, Master of Engineering (Morishima Lab)
2017.03 Waseda University, Bachelor of Engineering
2013.03 Waseda High School

I am interested in the fusion of AI (Artificail Intelligence) and HCI (Human-Computer Interaction), and would like to work to help improve human abilities by utilizing AI.
There are various ways of fusion. For example,  AI can support "tasks that are primarily performed by humans," such as improving human cognitive abilities and piano playing skills.  There are also human-in-the-loop learning such as Bayesian optimization and explainable AI, in which "humans interpret AI's processing or teach AI well from their prior knowledge.
I am interested in designing such systems in which AI and humans support each other well, and my mission is to implement such systems in applications and make them useful for human life. I would like to combine the engineering skills in the field of HCI that I learned as a student with the knowledge of AI that I have learned as a working adult, and work towards this goal.
My hobbies are sauna, travel, reading, listening to classical music, comic books, and games. I look forward to working with you.

Programming Language: Python, C#, C++, TypeScript, SQL, GO
Machine Learning: PyTorch, MLflow, Keras, Tensorflow
Computer Graphics: Unity, OpenGL, OpenCV, HoloLens
Web Development: AWS, Django, Flask, React, Vercel
Engineering: Git, Docker, k8s
Domain Knowledge: Computer science basis, Control engineering, Physics, Web performance tuning

Full paper (peer-eviewed)

1. Shoki Miyagawa, Atsuyoshi Yano, Naoko Sawada, Isamu Ogawa, High-Dimensional Bayesian Optimization with Constraints: Application to Powder Weighing, In Proc. of the 2022 Intl. Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’22).

2. Shoki Miyagawa., OptWedge: Cognitive Optimized Guidance towards Off-Screen POIs, In Proc. of the 2021 Intl. Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’21).

Short/Poster (peer-eviewed)

1. Ryo Shimamura, Seita Kayukawa, Takayuki Nakatsuka, Shoki Miyagawa, and Shigeo Morishima. 2019. A Study on the Sense of Burden and Body Ownership on Virtual Slope. In Proc. the 26th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR'19).

3. Shoki Miyagawa, Yuki Koyama, Jun Kato, Masataka Goto, and Shigeo Morishima. 2018. Placing Music in Space: A Study on Music Appreciation with Spatial Mapping. In Proceedings of the 2018 ACM Conference Companion Publication on Designing Interactive Systems (DIS '18 Companion). ACM, New York, NY, USA, 39-43.

4. Shoki Miyagawa, Yoshihiro Fukuhara, Fumiya Narita, Norihiro Ogata, and Shigeo Morishima. 2017. Retexturing under self-occlusion using hierarchical markers. In ACM SIGGRAPH 2017 Posters (SIGGRAPH '17). ACM, New York, NY, USA, Article 27, 2 pages.

• Community activity

  • Survey member of cvpaper.challenge (ECCV2022)

  • Visual Information Processing Camp Executive committee, Representative (VIP2017), Public Relation (VIP2018)

• Reviewer experience

1. IEEE BigData 2022

• Research internship 

  • Sony R&D (2018.2-3)

  • National Institute of Advanced Industrial Science and Technology (AIST) Mentor: Yuki Koyama, Jun Kato, Masataka Goto (2017.8-9)

• AI for Extracting and Transferring Experts' Tacit Knowledge（Sharing, 2020.10-2022.12）

• OngaACCEL (Sharing, 2016.09-2019.03)

• Japan Student Services Organization Scholarship for Top 30% Excellent Master Students（JPY1000,000, 2019.03）

• Shigeharu and Harue Okamoto Scholarship（JPY300,000, 2017.07）

• Graduate School of Advanced Science and Engineering Master's Program Scholarship（JPY100,000, 2017.07）

• TOEIC: 720 (2022.07)

• Coursera 

  • Generative Adversarial Networks (GANs) Specialization

  • Deep Learning Specialization

  • Machine Learning