CV

Education

The University of Tokyo, M.S. in Technology Management for Innovation, Graduate School of Engineering, Apr 2025 - Mar 2027 (expected)
The University of Tokyo, B.Eng. in Systems Innovation, Faculty of Engineering, Apr 2022 - Mar 2025 (transfer admission)

Ku Onoda, Paavo Parmas, Hiroki Furuta, Soichiro Nishimori, Yuta Oshima, Shohei Taniguchi, and Yutaka Matsuo. “Multi-Axis Max@K Reinforcement Learning for Representative Diversity in Text-to-Image Generation.” IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2027. Accepted. Paper · Code
Ku Onoda, Paavo Parmas, Manato Yaguchi, and Yutaka Matsuo. “Does ‘Do Differentiable Simulators Give Better Policy Gradients?’ Give Better Policy Gradients?” International Conference on Learning Representations (ICLR), 2026. Paper

Yuta Oshima*, Ku Onoda*, Yusuke Iwasawa, Masahiro Suzuki, Yutaka Matsuo, and Hiroki Furuta. “AutoRef: Harness Optimization for Agentic Multi-Reference Image Generation.” arXiv preprint, 2026. Paper · Code
* Equal contribution.

Ku Onoda, Yuta Oshima, Shohei Taniguchi, Soichiro Nishimori, Paavo Parmas, Hiroki Furuta, and Yutaka Matsuo. “Diversity-Aware Max@k Optimization for Improving Best-of-N Performance in Image Generation with Diffusion Models.” The 40th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI 2026), 2026. Paper
Ku Onoda, Paavo Parmas, and Yutaka Matsuo. “Efficient and Low Bias Policy Gradient Estimation in Contact Rich Differentiable Simulation.” The 39th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI 2025), 2025. Paper

JSAI Annual Conference Student Incentive Award, General Session, Oral Presentation Division, 39th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI 2025), May 2025
JGC-S Scholarship Foundation grant scholarship, Apr 2025 - Mar 2026