CV

Master of Science

KTH Royal Institute of Technology

Applied and Computational Mathematics

• Mathematics of Data Science track

Bachelor of Engineering

The University of Tokyo

Systems Innovation

• Exchange studies at KTH during August 2022 - June 2023

Master's Thesis Student at Division of Probability, Mathematical Physics and Statistics

KTH Royal Institute of Technology

Supervisor: Asst. Prof. Soon Hoe Lim.
Thesis Title: Planning as Conditional Generative Sampling: Belief- and Reward-Conditioned Diffusion Planners for Informative Path Planning

• Developed a conditional generative framework utilizing diffusion models (DDPMs) to sample high-reward trajectories for autonomous underwater vehicles.
• Evaluated the model’s out-of-distribution generalization, proving that feasible OOD conditioning allows the planner to synthesize novel behaviors absent from the training demonstrations.

Research Engineer at Physics of Medical Imaging Group

KTH Royal Institute of Technology

Supervisors: Prof. Mats Danielsson, Assoc. Prof. Mats Persson, Per Lundhammar

• Designed and implemented a permutation-equivariant deep learning model using Set Transformer to infer temporal ordering of unordered photon detection data in SPECT imaging.
• Reduced inference complexity from factorial time to a single forward pass while achieving competitive ordering accuracy for short chain lengths against a maximum likelihood baseline.

Research Assistant

National Ocean Policy Secretariat, Cabinet Office, Government of Japan

Supervisors: Prof. Toru Sato, Toshiro Suzuki, Takamasa Nakamura

• Developed a stochastic risk assessment model using Bayesian Monte Carlo simulations to quantify the frequency and magnitude of global mineral resource supply disruptions.
• Evaluated the economic security value of domestic mineral resource development by modeling the avoided production losses enabled by strategic stockpiling.

Bachelor's Thesis Student at Laboratory of Environmental Modeling and Synthesis

The University of Tokyo

Supervisor: Prof. Toru Sato.
Thesis Title: Proposal and cost evaluation of observation point placement method for underwater monitoring of sub-seabed CCS

• Developed a cost-efficient monitoring framework for offshore carbon capture and storage (CCS).
• Performed large-scale numerical simulations to analyze environmental impacts of CO₂ leakage.
• Designed and implemented a modified greedy solution for optimal coverage problems.

Cost assessment of optimal seawater monitoring for unexpected CO₂ leakage from an offshore reservoir

International Journal of Greenhouse Gas Control

Volume 146, pages 104455

Environmental Research Grant

Granted 50,000 SEK for a thesis project focused on environmental sustainability

Travel Grant

Granted 450,000 JPY to fund research presentations at the University of Bergen, Imperial College London, and Plymouth Marine Laboratory

Graduate Fellowship

Highly selective national scholarship (max. 3 recipients annually) granting 10,000,000 JPY covering two years of graduate studies, extendable for doctoral studies

Study Abroad Fellowship

Competitive scholarship granting 1,350,000 JPY awarded to support exchange studies at KTH Royal Institute of Technology