Pau Lopez
Senior Research Scientist at Universitat Autònoma de Barcelona
Spain
Summary
🤩
Rockstar🎓
Top SchoolPau Lopez is a Senior Research Scientist at Apple and adjunct professor at Universitat Autònoma de Barcelona with 12 years of experience building machine learning models that generalize from limited labels. His PhD in deep learning and computer vision and a magna cum laude AI master's from KU Leuven underpin a career spanning academic research, industry labs (Element AI, ServiceNow Research) and production-focused contributions. He combines theoretical rigor with hands-on engineering—evident in significant contributions to the tiny-dnn C++ framework where he implemented recurrent cell layers, improved testing and integration. Pau focuses on making AI learn more like humans to tackle high-impact problems, and he remains active in the research community as an ELLIS member and educator.
12 years of coding experience
3 years of employment as a software developer
(Advanced) Master's degree, Artificial Intelligence, Magna Cum Laude, (Advanced) Master's degree, Artificial Intelligence, Magna Cum Laude at KU LeuvenGraduate, Computer Engineering, Graduate, Computer Engineering at Universitat Autònoma de BarcelonaHigh School (Batxillerat), Science and Technology, High School (Batxillerat), Science and Technology at IES Puig de la Creu
Spanish, English, Catalan, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (13)
neural-network10
machine-learning10
rnn-model10
c-language10
deep-learning10
cprogramming-language10
n10
web-framework9
testing8
data-structure7
data-structures7
algorithm7
algorithms7
Programming languages (6)
Github contributions (5)
tiny-dnn/tiny-dnn
Jun 2017 - Aug 2017
header only, dependency-free deep learning framework in C++14
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:21 commits, 33 PRs, 2 branches in 2 months
Contributions summary:Pau made significant contributions to the `tiny-dnn` deep learning framework. They implemented recurrent cell layer functionality, including forward and backward propagation within the `recurrent_cell_op_internal.h` and `recurrent_cell_layer.h` files. Further contributions include generalizing gradient checks and fixing integration tests related to the recurrent layers. The user also addressed code style with clang format and improved test coverage and examples.
cppheaderdeep-learningc-plus-plusmachine-learning
ServiceNow/synbols-benchmarks
Nov 2020 - Apr 2021
Benchmarks for the Synbols project. Synbols is a ServiceNow Research project that was started at Element AI.
Contributions:23 commits, 2 PRs, 18 pushes in 5 months
benchmarkbenchmarksbenchmarking
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.