I am passionate about merging AI innovation with urban and business transformation. My goal is to create smarter, more sustainable cities and organizations. As the founder of an AI-focused LLC in Japan, I am eager to engage in business collaborations and projects that leverage machine learning to improve efficiency and sustainability.…

TETSUYA NAKAJIMA

I am passionate about merging AI innovation with urban and business transformation. My goal is to create smarter, more sustainable cities and organizations. As the founder of an AI-focused LLC in Japan, I am eager to engage in business collaborations and projects that leverage machine learning to improve efficiency and sustainability.…

Available to hire

I am passionate about merging AI innovation with urban and business transformation. My goal is to create smarter, more sustainable cities and organizations. As the founder of an AI-focused LLC in Japan, I am eager to engage in business collaborations and projects that leverage machine learning to improve efficiency and sustainability.

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Skills

Experience Level

ChatGPT
Expert
Python
Expert
PyTorch
Expert

Language

Japanese
Fluent
English
Advanced

Work Experience

Smart City Consultant at Oriental Consultants Global Co., Ltd.
September 30, 2024 - September 30, 2024
Provided consulting for smart-city planning and AI-based traffic systems in major Asian cities.
Deputy Director General at City of Yokohama – Climate Change Policy Headquarters
March 31, 2014 - March 31, 2014
Initiated and led the Yokohama Smart City Project, a pioneering public-private partnership involving major electric power and gas utilities.
Director General for Overseas Support at City of Yokohama – International Cooperation Bureau
January 1, 2016 - January 1, 2016
Advised Da Nang City (Vietnam) on urban planning and economic revitalization.
Chief Executive Officer at Yokohama Air Cargo Terminal Co., Ltd.
April 1, 2016 - May 31, 2019
Led management operations and digital transformation strategy of the terminal.
Auditor at Center for Construction Resource Recycling
August 31, 2021 - August 31, 2021
Conducted internal audits and advised on environmental resource utilization policies.
Project Manager at City of Yokohama
January 1, 2005 - January 1, 2005
Led the formulation of the Minato Mirai Redevelopment Plan and promoted urban revitalization projects.

Education

Master of Computer Science at Georgia Institute of Technology
September 1, 2021 - December 13, 2025
Master of Urban Planning at New York University
January 1, 1992 - January 1, 1992
Bachelor of Engineering at Hokkaido University
April 1, 1975 - March 31, 1980

Qualifications

E-Certificate (AI Engineer)
January 1, 2021 - November 15, 2025
G-Certificate (AI Business Implementation)
January 1, 2019 - November 15, 2025
Certificate of Appreciation
January 1, 2016 - November 15, 2025
World Smart City Award
January 1, 2011 - November 15, 2025
TOEIC
January 1, 2009 - November 15, 2025

Industry Experience

Government, Transportation & Logistics
    paper Reinforcement Learning EG. OverCooked
    Overcooked-AI: Multi-Agent Reinforcement Learning Project This project demonstrates a full implementation of Multi-Agent Reinforcement Learning (MARL) in the Overcooked-AI environment, a widely used benchmark for cooperative AI research. Project Summary • Implemented a MAPPO-based (Multi-Agent PPO) learning pipeline in Python. • Built a custom Gym wrapper for Overcooked-AI (2021 stable version). • Designed reward shaping, feature extraction, trajectory collection, and PPO training loops. • Agents successfully learned coordinated behaviors such as ingredient delivery and soup production. Technical Highlights • Environments: Overcooked-AI (Cramped Room, Asymmetric Advantages). • Algorithms: PPO / MAPPO, baseline rule-based agents for comparison. • Tools: PyTorch, NumPy, custom policy networks, action masking, logging utilities. • Features: Multi-agent state featurization, advantage estimation, value normalization. Results The learning curve below represents an example of agent improvement over early episodes. Agents progressively reduce collisions, optimize movement, and increase team reward.…

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