Daisuke Oda
Statistician
Chiyoda, Japan
Summary
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Rockstar🎓
Top SchoolDaisuke Oda is a statistician with 12 years of experience at the Japan Statistics Bureau, blending rigorous public-sector analytics with hands-on algorithm development. Trained in agricultural engineering at Tokyo University of Agriculture and Technology, he specializes in data analysis, sample design, GIS, VBA and R, and brings practical English proficiency to collaborative projects. An active open-source contributor, he has extended and tested core Markov-chain algorithms in well-known QuantEcon libraries (Julia and Python), adding robust implementations and unit tests for the GTH solver. After a life-changing injury he learned to adapt creatively—teaching himself programming, hand-only driving, and new skills alongside colleagues—demonstrating resilience and a collaborative spirit. He combines methodological depth with a pragmatic, optimistic approach to solving statistical and computational problems.
12 years of coding experience
Bachelor's degree, Agricultural Engineering, Bachelor's degree, Agricultural Engineering at Tokyo University of Agriculture and Technology
Stackoverflow
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Github Skills (11)
unit-testing10
numba10
markov-chain10
numerical-methods10
python10
julia10
testing10
linear-algebra9
integer-arithmetic9
rational-numbers9
optimization8
Programming languages (8)
Github contributions (5)
QuantEcon/QuantEcon.py
Aug 2014 - Jan 2023
A community based Python library for quantitative economics
Role in this project:
Back-end Developer
Back-end DeveloperContributions:109 reviews, 323 commits, 225 PRs in 8 years 6 months
Contributions summary:Daisuke primarily contributed to the development of the core algorithms within the `quantecon/quantecon.py` repository, with a focus on mathematical and statistical tools for quantitative economics. Their contributions included improving efficiency in existing algorithms, such as the calculation of stationary distributions for Markov chains, and addressing errors in indexing. They were also involved in testing and refining existing numerical methods, adding new functionality with the creation of a random tournament graph.
pythoncomputational-economicseconomics
QuantEcon/QuantEcon.jl
Nov 2014 - Jan 2023
Julia implementation of QuantEcon routines
Role in this project:Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:28 reviews, 77 commits, 61 PRs in 8 years 2 months
Contributions summary:Daisuke primarily contributed to the implementation and testing of a new function, `gth_solve`, for solving the stationary distribution of Markov chains using the Grassmann-Taksar-Heyman (GTH) algorithm. They added the `gth_solve` function, integrated it into the main codebase, and wrote corresponding unit tests, including cases for rational and integer elements and generator matrices. The user demonstrated proficiency in extending the codebase's functionality through algorithm implementation and thorough testing practices.
julia
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