David Haim is a Senior Forest Economist based in Portland, Oregon with 11 years of professional experience blending applied economics, natural resource management, and academic research. At Campbell Global he advances forest valuation and policy analysis, drawing on a PhD in Applied Economics and prior roles quantifying land-use leakage, wood-product demand systems, and public preferences for forest outcomes. He has taught environmental economics and econometrics at Oregon State University, evidencing strong communication skills and a knack for translating complex models to decision-makers and students. Unusually for his field, he contributes to C++ open-source projects—improving test coverage and executor efficiency in a modern concurrency library—bringing software engineering rigor to empirical research workflows. His background spans international research training from the University of Haifa to US-based program design, enabling interdisciplinary approaches to forest carbon and market challenges. David combines deep technical modeling expertise with practical policy insight to deliver actionable, well-tested economic analyses.
11 years of coding experience
3 years of employment as a software developer
B.A, Economics and Business Management, B.A, Economics and Business Management at University of Haifa
PhD, Applied Economics, PhD, Applied Economics at Oregon State University
Modern concurrency for C++. Tasks, executors, timers and C++20 coroutines to rule them all
Role in this project:
Back-end Developer
Contributions:10 releases, 20 reviews, 148 commits in 2 years 10 months
Contributions summary:David primarily contributed to improving the test suite for the concurrencpp library, focusing on result and executor testing. Their commits included improvements to existing tests and the addition of new tests for executors, ensuring better testing coverage and functionality. Furthermore, the user made code changes to executors to increase efficiency, code quality, and fixed compiler warnings. They also refactored and optimized existing code.
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