Gianluca Annunziata
IOS App Developer at Iriscube Reply
Castel San Giorgio, Campania, Italy
Summary
🤩
Rockstar🎓
Top SchoolGianluca Annunziata is an iOS app developer with 8 years of software engineering experience and a strong academic background in Data Science and Artificial Intelligence from the University of Salerno. He combines mobile development at Iriscube Reply with past R&D experience at Ericsson and hands-on machine vision and ML projects, including a robot-vision SmartDobot and a Web IDE UI/UX enhancement for academic tooling. A Python enthusiast and full-stack contributor, he built QualityScaler—an image/video AI upscaler with CPU/GPU backends and a polished GUI—demonstrating his ability to integrate deep learning models, OpenCV, and CUDA into user-facing apps. Based in Campania, Italy, he blends practical product-focused iOS work with research-minded skills in computer vision and data-driven engineering, often surfacing non-obvious performance considerations when moving models from prototype to production.
8 years of coding experience
1 year of employment as a software developer
Laurea triennale in Scienze e Tecnologie Informatiche, Informatica, 89, Laurea triennale in Scienze e Tecnologie Informatiche, Informatica, 89 at Università degli Studi di Salerno
Github Skills (21)
pytorch10
opencv10
python10
video-processing10
gui-application10
super-resolution10
cuda10
image-processing9
onnx9
360-video9
windows9
deeplearning-ai9
deep-learning9
jpeg8
webp8
Programming languages (3)
Github contributions (5)
Djdefrag/QualityScaler
Apr 2022 - Jan 2023
QualityScaler - image/video AI upscaler app
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:49 releases, 137 commits, 4 PRs in 9 months
Contributions summary:Gianluca developed the "QualityScaler" application, focusing on image and video upscaling using a GUI. They implemented various features, including drag-and-drop functionality, support for different upscale factors (x1, x2, x4, auto), and compatibility with various image and video formats. Their work involved both CPU and GPU backends (CUDA), demonstrating proficiency in integrating deep learning models with a user-friendly interface using Python, OpenCV, and potentially PyTorch/ONNX.
amdanimecompression-artifact-reductiondeep-learningdirectx-12
Djdefrag/NiceScaler
Feb 2022 - Oct 2022
Contributions:6 releases, 33 commits, 33 pushes in 8 months
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