Josep De Cid Rodríguez
Software Engineer at DataArt
Catalonia, Spain
Summary
🤩
Rockstar🎓
Top SchoolJosep De Cid Rodríguez is a software engineer with a decade of experience blending full-stack development and AI research, currently at DataArt after roles as Full Stack Engineer and CTO. He holds a strong academic background in computer science and a master's in Artificial Intelligence from UPC, and has taught and researched at the university and supercomputing center level. Josep has led engineering and AI integration for a rural tourism marketplace as CTO, demonstrating product-minded architecture and team leadership. As an open-source ML engineer he contributed substantive refactors to the widely used pytorch-grad-cam project, modernizing compatibility and reliability for vision explainability tools. Comfortable shipping both backend systems and neural-network code, he also enjoys game development as a creative outlet—aiming to make things more fun than an Atari Expansion Pak. Based in Catalonia, he combines research-grade ML skills with practical production experience across startups and research institutions.
10 years of coding experience
8 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Innopolis UniversityUPC Universitat Politècnica de Catalunya
Spanish, Catalan, English
Stackoverflow
1,767reputation
102kreached
76answers
12questions
pytorch
top-5%
Github Skills (11)
computer-vision10
pytorch10
deeplearning-ai10
deep-learning10
python10
machine-learning9
neural-network6
keras6
lstm6
javascript6
tensorflow6
Programming languages (7)
Github contributions (5)
jacobgil/pytorch-grad-cam
Jan 2020 - Oct 2021
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 4 PRs, 2 branches in 1 year 9 months
Contributions summary:Josep's commits primarily focused on refactoring and improving the Grad-CAM implementation for computer vision tasks. They updated the code to be compatible with newer versions of PyTorch, removed deprecated features, and migrated custom autograd functions to meet new static requirements. The user also addressed code style issues and made adjustments to the package's setup for clarity and consistency, solidifying the functionality of the package.
score-camxaiimage-segmentationimage-similarityclass-activation-maps
josepdecid/BachPropagation
Mar 2019 - Apr 2019
Contributions:99 commits, 50 pushes, 2 branches in 1 month
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