Martin Raison
Cofounder & CTO at Nabla
France
Summary
🤩
Rockstar🎓
Top SchoolMartin Raison is a seasoned engineering leader and co-founder/CTO with 13 years of experience building production-grade AI and NLP systems, now leading Nabla’s effort to deploy ambient clinical AI that generates notes and medical coding across specialties. He combines research-grade expertise from Stanford and Meta AI with hands-on product engineering honed at Wit.ai and Facebook, shipping scalable back-end systems and integrations. His open-source work includes contributions to Stanford’s SNAP graph library (C++ performance and graph/table primitives) and improving Python SDK build/release automation for Wit.ai, reflecting both low-level optimization and tooling chops. Comfortable moving between research, infrastructure and product, he’s known for making complex data processing and graph algorithms practical in production. Based in Paris, he pairs deep academic training with startup grit and a track record of turning NLP research into clinical impact.
13 years of coding experience
6 years of employment as a software developer
Diplôme d'Ingénieur Informatique, Diplôme d'Ingénieur Informatique at École PolytechniqueMaths & Physics, Maths & Physics at Lycée Ste GenevièveMaster of Science (MSc) Computer Science, Master of Science (MSc) Computer Science at Stanford University
Stackoverflow
1,047reputation
21kreached
19answers
8questions
Github Skills (27)
algorithm10
dependency-management10
algorithms10
graph-algorithms10
c-language10
python10
data-structure10
build-automation10
data-processing10
data-structures10
cprogramming-language10
curl10
testing9
cicd9
performance-optimization9
Programming languages (18)
Github contributions (5)
wit-ai/pywit
Sep 2014 - Dec 2014
Python library for Wit.ai
Role in this project:
Automation Engineer / Build & Release Engineer
Automation Engineer / Build & Release EngineerContributions:1 release, 12 commits, 1 push in 2 months
Contributions summary:Martin focused on automating the build and release process for the PyWit SDK. They implemented changes to the `setup.py` file to build the project, fetch necessary dependencies from GitHub releases (specifically libwit), and integrate platform-specific libraries. Their work involved managing dependencies, adapting build scripts, and ensuring the project could be built and packaged correctly, improving the overall build process. Furthermore, the user implemented a cleanup step as part of the build process to reduce overhead.
python
snap-stanford/snap
Feb 2013 - Dec 2013
Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library.
Role in this project:Back-end Developer
Back-end DeveloperContributions:25 commits in 9 months
Contributions summary:Martin primarily contributed to the development and testing of a specialized graph analysis library. They added tests for graph construction, implementing and refining data structures and algorithms within the SNAP framework. The user's work involved creating and manipulating data tables, including operations like joining, selecting, and grouping, showcasing their expertise in data processing and graph-related algorithms. Furthermore, the user optimized the underlying code for efficient memory management, demonstrating an understanding of performance optimization in C++.
graph
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