Imad Toubal
Software Engineer at Waymo
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolImad Toubal is a software engineer and computer vision researcher with 11 years of experience, currently building vision models for traffic control at Waymo in San Francisco. He holds advanced degrees from the University of Missouri and has a strong research background in biomedical image segmentation, geospatial building change detection (SpaceNet top graduate team), deepfake detection with a public web tool, and age estimation. Imad has multiple Google research stints including a CVPR 2023 paper and a patent contribution, and he contributes to open-source CV tools—improving the popular face-alignment library with batch processing and robust BlazeFace fixes. Comfortable moving ideas into production, he has experience across big data, A/B experimentation, and full-stack deployments. Outside work he applies his skills to video game development, reflecting a practical blend of systems engineering and creative coding.
11 years of coding experience
6 years of employment as a software developer
Master of Science - MS Computer Engineering, Master of Science - MS Computer Engineering at Institute of Electrical and Electronics Engineering (Ex: INELEC) BoumerdesUniversity of Missouri
French, English, Arabic
Stackoverflow
51reputation
209reached
0answers
1question
Github Skills (9)
face-detection10
computer-vision10
pytorch10
deep-learning10
python10
face-alignment10
image-processing9
tensorflowjs6
javascript6
Programming languages (6)
Github contributions (5)
1adrianb/face-alignment
Jul 2020 - Oct 2020
:fire: 2D and 3D Face alignment library build using pytorch
Role in this project:
ML Engineer
ML EngineerContributions:8 commits, 3 PRs, 6 comments in 3 months
Contributions summary:Imad primarily contributed to the face-alignment library by adding functionality for batch image processing. They implemented methods to process batches of images and detect faces, integrating the SFD face detector. Furthermore, the user incorporated the BlazeFace detector and fixed a bug related to portrait-oriented images within the BlazeFace implementation. This work focused on enhancing the library's capabilities for efficient face detection and landmark alignment, particularly in different image orientations.
pytorchpython3d-face-alignmentdeep-learningface-alignment
imadtoubal/Pytorch-Flask-Starter
Dec 2019 - Oct 2020
🐍+🔥This project is aimed to help Pytorch machine learning developers to quickly build a Flask web app in a Docker container ready to be deployed.
Contributions:44 commits, 2 PRs, 34 pushes in 10 months
pytorchpythondeep-learningflaskflask-web
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