Guillem Visa
Artificial Intelligence Researcher at Two Sigma
England, United Kingdom
Summary
👤
Senior🎓
Top SchoolGuillem Visa is an AI researcher and data scientist with 12+ years applying computer vision and machine learning to production problems, currently at Two Sigma in London. He holds a PhD in Image Processing/Computer Vision from Universitat Politècnica de Catalunya, complemented by engineering work at MIT and a business degree from Universitat de Barcelona, blending deep technical rigor with business sense. His career includes hands-on roles at Palantir and early work building broadcast and multiscreen video systems, giving him rare end-to-end experience from research prototypes to deployed analytics. Guillem is an active open-source contributor to scikit-image, where he optimized and hardened the widely used SLIC superpixels implementation, demonstrating attention to performance and maintainability. He combines strong algorithm design and multi-language programming skills with practical deployment experience in finance-grade ML systems.
12 years of coding experience
12 years of employment as a software developer
Final Degree Project, Communications, Final Degree Project, Communications at Massachusetts Institute of TechnologyBatxillerat, Batxillerat at Aula Escola EuropeaUPC Universitat Politècnica de CatalunyaDiplomatura, Business Studies, Diplomatura, Business Studies at Universitat de Barcelona
English, French, German, Catalan, Spanish
Stackoverflow
1reputation
80reached
0answers
1question
Github Skills (13)
c1710
computer-vision10
scikit-image10
c1110
python10
cython10
image-processing10
numpy10
data-structure9
algorithm9
data-structures9
algorithms9
azure-application-insights6
Programming languages (2)
Github contributions (5)
scikit-image/scikit-image
Dec 2013 - Jan 2014
Image processing in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:12 commits in 28 days
Contributions summary:Guillem primarily focused on implementing and refining the SLIC superpixels algorithm, a core component of the image processing library. Their contributions included enforcing connectivity constraints, optimizing the code, and introducing parameters for fine-grained control. These changes involved the creation of new functions, modification of existing ones, and adjustments to tests to ensure the algorithm's correct behavior. The user demonstrated proficiency in optimizing performance within the existing codebase.
image-processingpythoncomputer-visionimage
guillempalou/scikit-cv
Dec 2013 - Mar 2014
Contributions:54 commits in 3 months
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