Lucas Zeer
Greater Mexico City, State of Mexico
Summary
🤩
Rockstar🎓
Top SchoolLucas Zeer is a multidisciplinary engineer blending 11 years of software, hardware and design experience across nanotechnology, toy design and full-stack development. He has shipped production systems and automation for startups and enterprises—from contributing full-stack UI and backend improvements to NVIDIA's popular DIGITS deep learning platform to building microfluidic control software and optical sensor systems. Comfortable across JavaScript, Python, C++ and Ruby, he pairs web and ML tooling (Node, Rails, React, TensorFlow.js) with low-level electronics and signal-processing expertise. A founding member of Milan-based JellyFish Fab and cofounder of The Brainery, he moves easily between product design, embedded control and cloud services to solve real-world automation problems. Currently completing a Masters in Toy Design while building AI-driven educational games and food-automation software, he brings a rare combination of creative design thinking and rigorous systems engineering.
11 years of coding experience
3 years of employment as a software developer
Specializing Masters 1st Level, Design for Kids and Toys, Specializing Masters 1st Level, Design for Kids and Toys at Politecnico di MilanoBachelor of Applied Science (B.A.Sc.) , Nanotechnology, Bachelor of Applied Science (B.A.Sc.) , Nanotechnology at University of Waterloo
Github Skills (12)
torch-hub10
machine-learning10
caffe10
torch-net10
deep-learning10
python10
flask-ask9
flask9
uid8
front-end-development8
ui-design8
git5
Programming languages (13)
Github contributions (5)
NVIDIA/DIGITS
Jun 2016 - Aug 2016
Deep Learning GPU Training System
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:11 commits, 20 PRs, 2 pushes in 2 months
Contributions summary:Lucas primarily focused on improving the user interface and backend functionality related to the "Pretrained Model" feature. They implemented and modified the UI, including adding a "Make Pretrained Model" button and removing local storage usage. They also refactored the backend code, moving functions and updating file paths, while also adding the ability to download pretrained models. Their contributions touched upon both frontend templates and backend logic, demonstrating full-stack capabilities.
deep-learninggputorchmachine-learningtraining
Lucaszw/eth-red
Oct 2017 - Oct 2017
Contributions:27 commits, 3 PRs, 26 pushes in 1 day
ethereumblockchainweb3node-red
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