AI Specialist | Industrial Digitalization | Production Systems
Real time computer vision systems • Industrial AI & Offshore Digitalization • 100% Uptime in High Pressure Broadcast Ops • Predictive Modeling
📧 omargobranai@gmail.com | 💼 LinkedIn | 🐙 GitHub
AI Specialist with hands on experience in industrial digitalization, real time computer vision systems, and automation solutions.
I develop AI powered monitoring systems for offshore infrastructure and have operated computer vision tracking systems for international broadcast operations (UEFA). My expertise spans time series forecasting, computer vision, and chatbot based automation, with a proven track record maintaining 100% system uptime in high pressure environments.
Current focus: AI Engineering and Industrial Digitalization where I can bridge cutting edge ML with enterprise scale deployment.
| Project | Description | Tech Stack |
|---|---|---|
| RL Vehicle Routing | Deep Q Network for dynamic traffic optimization. Simulated 1,200 node network, achieved 28% reduction vs greedy algorithms. | PyTorch, DQN, Experience Replay |
| Super Resolution QR | Signal recovery with GANs/CNNs for degraded QR codes. 90% accuracy in reconstruction for industrial scanning. | PyTorch, GANs, Computer Vision |
| FootStats Analytics | End to end sports analytics with Dash dashboards, synthetic data generation, and statistical modeling. | Dash, Plotly, Scikit learn |
May 2022 – March 2026 | Vienna, Austria
Live Broadcast Computer Vision | UEFA & Austrian Bundesliga
Operated live computer vision and optical tracking systems for UEFA Champions League and Austrian Bundesliga matches Maintained 100% system uptime with zero delays across 3+ years of high pressure international broadcast operations Executed pre match calibration and signal flow validation protocols to prevent failures during live events Applied systematic troubleshooting methodologies to resolve hardware/software integration issues in real time
April 2023 – March 2024 | Hamburg, Germany
Industrial AI | Offshore Operations | Azure | Cognite Data Fusion
Developed AI based time series monitoring systems using Cognite Data Fusion for automated pressure estimation at Norwegian offshore facilities Designed and deployed "Non Ops Toolbox" a Dash/Plotly application for energy production data visualization with statistical outlier detection; reduced reporting time from days to minutes Supported Azure OCR machine learning pipeline for automated data extraction from 50+ monthly engineering reports; saved 40+ hours of manual data entry per month Led data literacy initiatives with training programs across 3 business units to introduce digital best practices
Bachelor of Science (BSc) in Artificial Intelligence
Johannes Kepler University - Linz, Austria (2026)
Focus Areas: Machine Learning, Deep Learning, Reinforcement Learning, Computer Vision, NLP, Time Series Analysis, Optimization
Certifications:
Create Machine Learning Models - Microsoft (Apr 2023)
Generative AI Learning Path - Google Cloud (Jul 2023)
Languages: Python, SQL, C#
AI/ML: PyTorch, TensorFlow, Scikit learn, Pandas, NumPy, Computer Vision
Cloud & Data: Microsoft Azure, Cognite Data Fusion, FastAPI
Visualization: Dash, Plotly
Languages: English (Native), Arabic (Native), German (C1)
Exploring opportunities in AI Engineering and Industrial Digitalization, particularly in energy sector AI, real time systems, or high scale production environments.