Emanuele Plebani
Senior Deep Learning Engineer at Imagry | Autonomous Driving
Palo Alto, California, United States
Summary
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Senior🎓
Top SchoolEmanuele Plebani is a Senior Deep Learning Engineer with a decade of experience building production-ready computer vision and ML systems, now based in Palo Alto. He holds a PhD from Purdue where he specialized in segmentation for medical and hyperspectral imaging with an emphasis on open-world and zero-shot scenarios, and previously helped industrialize tiny-ML workflows at STMicroelectronics by kickstarting the Cube.AI toolchain for MCU deployment. His background spans the full ML lifecycle—from model research (U-Nets, Bayesian uncertainty, transformers) to embedded C/C++ optimizations and cloud-scale service design at Amazon and Meta. Emanuele blends research rigor with pragmatic engineering: he has authored patents and production backends that squeeze neural networks into ultra-low-energy devices while also shipping LLM-based APIs and AI shopping features. An active contributor to community projects (e.g., expanding GAN documentation and visualizations), he combines domain expertise in autonomous driving 3D detection with an eye for interpretable, uncertainty-aware models. Colleagues describe him as someone who translates hard research problems into deployable, measurable products across both edge and cloud environments.
10 years of coding experience
15 years of employment as a software developer
Bachelor + Master of Science (M.Sc.) Computer Engineering, Bachelor + Master of Science (M.Sc.) Computer Engineering at Politecnico di MilanoDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Purdue University
Italian, English
Stackoverflow
101reputation
4kreached
5answers
0questions
Github Skills (13)
machine-learning10
python10
matplotlib9
seaborn7
opencv6
mnist6
tensorflow6
feature-extraction6
gpu6
jinja26
numpy6
lasagne6
github5
Programming languages (8)
Github contributions (5)
hindupuravinash/the-gan-zoo
Apr 2017 - Jan 2018
A list of all named GANs!
Role in this project:
ML Engineer
ML EngineerContributions:21 commits, 20 PRs, 2 comments in 9 months
Contributions summary:Emanuele primarily contributed to the project by adding new GAN models and improving the visualization of the data. They added the names of various GAN models into a file, updating the README and figure illustrating the cumulative number of GAN papers over time. The user also fixed rendering issues in the cumulative GAN histogram. The changes reveal a focus on expanding the project's scope and improving the clarity of the data.
pytorchdeep-learninggenerative-adversarial-networkmachine-learninggan
Banus/umf_unet
Nov 2021 - Dec 2022
Contributions:8 commits, 10 pushes, 1 branch in 1 year 1 month
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