Blockchain Programme Manager And Senior Researcher at The University of Edinburgh
City of Edinburgh, Scotland, United Kingdom
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Summary
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Senior
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Top School
Mojtaba Tefagh is a blockchain programme manager, founder and senior researcher blending eight years of hands-on algorithmic expertise with strategic industry engagement across academia and startups. Based in Edinburgh, he leads commercialization and partnership efforts at the University of Edinburgh’s Blockchain Technology Laboratory while founding Cairnlytics, a metadata-driven tool that preempts open-source supply-chain failures. A Stanford PhD in Electrical Engineering with dual BS degrees in Computer Science and Mathematics, he moves fluidly between optimization research and practical blockchain productisation—evidenced by contributions to the widely used COBRA Toolbox where he integrated advanced flux-consistency algorithms. He has steered technical teams for sustainable tokenization markets and co-founded an optimization lab, reflecting a rare mix of applied maths, software engineering and policy-facing outreach. Known for translating complex computational methods into deployable decentralisation metrics (like the Edinburgh Decentralisation Index), he combines rigorous research with a builder’s instinct for risk-focused tooling.
8 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Sharif University of Technology
Mathematics, Mathematics at Young Scholars Club
Doctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at Stanford University
The COnstraint-Based Reconstruction and Analysis Toolbox. Documentation:
Role in this project:
Back-end Developer & Algorithm Specialist
Contributions:22 commits, 5 PRs, 15 comments in 2 months
Contributions summary:Mojtaba focused on integrating and refining algorithms within the COBRA Toolbox, specifically for constraint-based modeling. Their commits demonstrate a deep understanding of flux consistency algorithms, integrating `swiftcore` and related methods into the `createTissueSpecificModel` and `findFluxConsistentSubset` functions. They also added new functionalities like `swiftGapFill` and `QFCA` algorithms, indicating a focus on expanding the toolbox's capabilities. The user was also involved in test and dependency checks.
Contributions:2 releases, 34 commits, 28 pushes in 4 years 3 months
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