Jordi Orri
Head Of Machine Learning at AMPHICO
Barcelona, Catalonia, Spain
Summary
👤
Senior🎓
Top SchoolJordi Orri is a Head of Machine Learning and tech founder with a Cambridge PhD and a decade of experience building ML-driven products for sustainable materials and energy applications. He has led a £2.5M industrial research programme and scaled ML teams while previously taking Amphicolor from PoC to product with full-stack production deployments that cut operational errors from 70% to 1%. As co-founder and former CTO at a VC-backed startup, he translated materials science into commercial biotech solutions (PFAS alternatives) and secured grant and investor backing. His research at Cambridge produced high-impact publications and open-source tools for multidimensional electron microscopy, and he improved testing infrastructure on notable scientific repos like hyperspy. Jordi blends deep domain knowledge in physics and chemistry with hands-on engineering (FastAPI, NextJS, AWS, Docker) and a track record of automating legacy processes to create digital twins and synthetic data at scale. He is equally comfortable supervising graduate researchers and shipping production ML systems that accelerate market entry and scientific discovery.
10 years of coding experience
6 years of employment as a software developer
MRes + PhD, Physics, MRes + PhD, Physics at University of CambridgeBachelor of Science - BS, Physical Chemistry, Bachelor of Science - BS, Physical Chemistry at Maastricht Science Programme
Catalan, Spanish, English, French
Github Skills (7)
testing10
pytest10
python10
data-analysis10
data-visualization4
data-visualisation4
data-visualizations4
Programming languages (3)
Github contributions (5)
hyperspy/hyperspy
Jan 2021 - Feb 2021
Multidimensional data analysis
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:5 reviews, 10 commits, 3 PRs in 10 days
Contributions summary:Jordi primarily focused on enhancing the testing infrastructure within the `hyperspy/hyperspy` repository. Their contributions involved creating and modifying tests for the spike removal tool functionality. The commits showcase the user's ability to write tests for both interactive and non-interactive modes, including masking, and incorporating various test parameters to ensure the tool's robustness and reliability. Additionally, the user updated the test code to improve code coverage, and ensure the tests align with other recent updates.
multidimensional-datapythondata-visualizationdata-analysismulti-dimensional
LorenzoPeri17/nanoDTC
May 2020 - Dec 2021
Repository to teach GitHub to NanoDTC students.
Contributions:27 commits in 1 year 7 months
teach
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