About Me
I'm from Yokohama, Japan. My background is in Civil Engineering, specifically in Construction Engineering and Management, and Machine Learning. I am interested in changing an industry that is spiraling into its most uncertain age due to labor shortages, rising costs, and increased demand for building new buildings as well as maintaining old buildings and infrastructure. My current focus is advancing MLLM capabilities for construction specific domains.
Experience
Satellite 1 (Concourse D) Project at O'Hare International Airport — Midfield Cooling Plant (MCP) and Hydronic Piping systems.
M.S. thesis research in the RAAMAC Lab on automating document recognition and quantity take-offs using machine learning. Researched BIM workflows and used Revit to build ML datasets for domain-specific automated drawing recognition. Teaching Assistant for CEE 320: Construction Engineering.
Embedded software engineer on middleware. Authored design documents and developed an in-vehicle API for a proof-of-concept application using C++, Python, and Bazel.
Chicago O'Hare Modernization Project (Terminal 5) — AECOM Hunt × Clayco × Bowa joint venture. Managed change orders, cost-loaded schedules, BIM coordination, RFIs, and Submittals on a $100M+ project.
Localized the Reconstruct platform for the Japanese market, liaising directly with Ōbayashi（大林）, JR East（JR東日本）, and the Ministry of Land, Infrastructure, Transport and Tourism（国土交通省）. Studied VDC workflows and project management under senior engineers.
Contributed to the Benck Family Agricultural Interpretive Center project.
Computer vision and ML research for quality control of pre-pour concrete slabs. Built automated rebar inspection tools including gap analysis and rebar detection models.
Assisted graduate research on fly ash properties in concrete formation for the CEE Department. Ran calorimeter tests to measure heat curves of fly ash in concrete.
Education
Dual-language diploma programme in English and Japanese.
Minor in Computer Science.
Thesis-based M.Sc in the RAAMAC Lab — machine learning applications in construction engineering and management.