Amir Kaviani, MEng

Amir Kaviani, MEng

About

Detail

IT Technician | Networking & Technical Support | Onsite & Client Support
Canada
Contact Amir regarding: 
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Full-time jobs
Starting at CAD24/hour ~USD16.8/hour

Timeline

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Résumé

Jobs verified_user 0% verified
  • Great River Financial Services Inc
    Information Technology Field Technician
    Great River Financial Services Inc
    Apr 2025 - Current (1 year 7 months)
    Engineering
  • Kognitive Sales Solutions
    Field Marketing Representative
    Kognitive Sales Solutions
    Aug 2024 - Mar 2025 (8 months)
    Sales
  • NRDC Naji Research and Development Company
    Information Technology Support Analyst
    NRDC Naji Research and Development Company
    Dec 2021 - Dec 2023 (2 years 1 month)
    Engineering
Education verified_user 0% verified
  • University of Science and Culture
    Bachelor of Engineering - BE, Computer Software Engineering
    University of Science and Culture
  • University Of Windsor
    Master of Engineering - MEng, Electrical And Computer Engineering
    University Of Windsor
Projects (professional or personal) verified_user 0% verified
  • F
    Face Mask Detection System
    Jan 2022 - Current (4 years 10 months)
    • Developed a real-time computer vision application to detect face mask compliance using CNNs and OpenCV.
    • Trained and fine-tuned deep learning models on image datasets to achieve >95% detection accuracy.
    • Deployed the system on embedded devices for low-latency edge inference in public safety scenarios.
  • D
    Defect Detection using Convolutional Neural Networks
    Jan 2022 - Current (4 years 10 months)
    • Developed a CNN pipeline to classify and localize defects in industrial components, improving detection accuracy to 92%.
    • Optimized algebraic operations in training and inference for efficiency on GPU/embedded targets, gaining practical exposure to compiler-level optimization.
  • A
    Automotive License Plate Detection System
    Jan 2022 - Current (4 years 10 months)
    • Designed and deployed a convolutional neural network (CNN) model for license plate recognition, optimized for real-time inference on edge devices.
    • Enhanced data preprocessing and implemented runtime optimizations using Python and C++, achieving a 25% reduction in latency compared to baseline models.
    • Collaborated on hardware integration and simulation to validate model performance on embedded automotive platforms for practical deployment.