Andrea Palazzi
Head Of Artificial Intelligence at Nomitri
Berlin, Germany
Summary
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Rockstar🎓
Top School
Top expert inAutonomous Robotics and Simulation Technology
Andrea Palazzi is Head of Artificial Intelligence at Nomitri in Berlin with 12 years of experience and a PhD in Computer Vision. He blends deep academic research—work on driver gaze prediction, image/video saliency, differentiable rendering and synthetic data—with hands-on productization. At Nomitri he has led full model lifecycles, built internal deep learning infrastructure and CI pipelines, and specializes in quantization for on-device deployment. His open-source work includes a lane-detection module for a self-driving car project that implements temporal smoothing to boost robustness across frames. He is known for turning research breakthroughs into reliable, embedded AI systems.
13 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Vision, Doctor of Philosophy - PhD, Computer Vision at Università degli Studi di Modena e Reggio Emilia
Italian, English, German, French
Stackoverflow
1,604reputation
286kreached
36answers
0questions
urllib2
top-5%
google-drive-api
top-5%
python
top-5%
Github Skills (16)
computer-vision10
opencv10
opencv310
opencv210
python10
hough-transform10
image-processing10
google-drive-api9
urllib29
deep-learning8
tensorflow28
tensorflow8
pydrive6
machine-learning6
numpy6
Programming languages (6)
Github contributions (5)
ndrplz/self-driving-car
Dec 2016 - Oct 2020
Udacity Self-Driving Car Engineer Nanodegree projects.
Role in this project:
Software Engineer (Computer Vision Focus)
Software Engineer (Computer Vision Focus)Contributions:237 commits, 5 PRs, 218 pushes in 3 years 10 months
Contributions summary:Andrea contributed to a self-driving car project, specifically focusing on lane detection. Their primary contribution involved creating and implementing the `lane_detection.py` module, which includes core functions for image processing, Hough line detection, and lane line fitting. The user's work showcases expertise in computer vision techniques such as edge detection, Gaussian blurring, and image masking. The module also incorporated a temporal smoothing mechanism to improve the robustness of lane detection across multiple frames.
pytorchnanodegreeself-driving-car-engineerudacity-self-driving-carudacity
ndrplz/small_norb
Dec 2017 - Feb 2022
Python wrapper to small NORB dataset
Contributions:23 commits, 7 PRs, 11 pushes in 4 years 2 months
pythonnorbnorb-datasetpython-wrapperdataset
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