Mahmoud Almasri

Object detection & classification using AI • Build, mentor, and lead a team of data ENGINEER & analysts • Collect, Clean, and Analyze data in real time. • Containerized and deployed scalable microservices in Kubernetes • Built data pipelines to process high-volume telemetry • Automated CI/CD and monitoring (Prometheus/Grafana) for zero-downtime updates

Drones’ Inter-operator cellular connectivity service by learning and prediction Predicting cellular connectivity of drones using AI • Collect, Clean, and Analyze real time series data. • Handling 1TB of data daily. • Improved data processing speed by 40% with distributed computing tools. • Develop and implement models for predictive analytics, enhancing decision-making of drones.

Drone Detection and classification based on time series data using AI • ML data management (collect, store, manage data), • Creating training datasets (data labeling, data augmentation, feature engineering, data partitioning, sampling and slicing • Familiarity with architectural choices for ML & DL systems. • Use NVIDIA Jetson AGX Xavier to develop end-to-end AI model for drone detection & Identification.

Intelligent Spectrum Allocation: - Designed reinforcement learning (RL) algorithm for intelligent spectrum allocation to secondary unlicensed users with multiple criterion optimization Self-organized energy efficient network: - Development of RL algorithm for classical and combinatorial multi-armed framework - Game theory and Graph theory for decentralized network with local information flow to tackle massive networks - Hidden Markov Model (HMM) algorithm and multi-armed bandit learning with massive real HF measurement datasets to develop and test cognitive radio application for HF band. Skills & tools used: - Programming skills: Matlab & Simulink, Python, C++, Latex

Signal acquisition algorithm for Ultra Wide-band communication systems.