Khaled Bedda

Data Scientist & AI Engineer

Transforming complex data into actionable insights and building intelligent systems that drive innovation. Specializing in distributed AI, federated learning, and MLOps.

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About Me

I'm a passionate Data Scientist and AI Engineer with 3+ years of experience developing and deploying machine learning solutions across healthcare, government, and industrial IoT sectors.

My expertise spans from research-based distributed AI systems to production-ready MLOps pipelines. I thrive on bridging the gap between cutting-edge AI research and real-world business applications.

Currently leading AI initiatives at Rivercity Innovations, where I develop temperature anomaly detection systems for cold-chain monitoring, directly impacting enterprise operations and efficiency.

5 Published Papers

280+ People Trained

40% Improved Accuracy

$200K+ Funding Secured

Technical Expertise

AI & Machine Learning

TensorFlow PyTorch scikit-learn OpenCV Federated Learning

Programming

Python R C/C++ CUDA MATLAB

Cloud & MLOps

AWS Azure Docker MLflow Kubeflow

Data & Visualization

Pandas NumPy Matplotlib PowerBI SQL

Professional Journey

Data Scientist

Rivercity Innovations

May 2025 - Present

Leading AI initiatives for cold-chain monitoring systems. Developed temperature anomaly detection framework reducing false alerts by 40%.

AI Tools & Infrastructure Engineer

Canada Revenue Agency

Aug 2023 - Mar 2025

Provided technical leadership for infrastructure supporting 1,000+ analysts. Led AI governance framework development.

Graduate Research Assistant

Thunder Bay Regional Health Research Institute

Sep 2021 - Jan 2023

Conducted research on Distributed AI for 5G Networks. Published 3 first-author papers in IEEE conferences.

Featured Projects

🚗

Autonomous Vehicle System

Real-time lane detection and object recognition using ESP32, Flask, and OpenCV. Achieved 85% accuracy in controlled environments.

OpenCV Flask ESP32 Python

🧠

EEG Classification with VAE

Developed generative models to address data imbalance, improving classification accuracy from 78% to 89% on medical datasets.

VAE TensorFlow Medical AI Python

🌡️

Motor Temperature Prediction

Comprehensive ML pipeline comparing regression, tree-based, and RNN models, achieving 92% accuracy and reducing maintenance costs by 15%.

Time Series RNN Industrial AI Python

📡

Federated Learning for 5G

Research on peer-coordinated sequential split learning for intelligent traffic analysis in mmWave 5G networks.

Federated Learning 5G Networks PyTorch Research

Let's Connect

I'm always interested in discussing AI/ML innovations, research collaborations, and exciting opportunities. Feel free to reach out!

khaledbedda12@gmail.com +1 807-358-7144 LinkedIn GitHub