ISSUE 03 | BLOG

#extracurricullar

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  • Reaching 98% accuracy using machine learning to classify biomechanical gait segments

    Mar 18, 2026

    Using temporal convolutional networks to segment gait cycles and extract clinically meaningful recovery metrics from wearable sensor data.

    engineeringsoftwarebiomedicalextracurricullarmachine-learningproject
  • Strengthing the connection between patients and physiotherapists using a mobile application

    Mar 18, 2026

    A McMaster Biomedical Engineering Technical Team (BMETT) project focused on building full-stack systems, ML pipelines, and firmware to enhance musculoskeletal rehabilitation.

    engineeringsoftwarebiomedicalextracurricullarmobile-development
  • Leading full-stack, machine learning, and firmware development

    Mar 8, 2026

    Leading a team competing against 10 universities across Canada — building full-stack systems, ML pipelines, and firmware all at once.

    engineeringsoftwarebiomedicalextracurricullarmachine-learningfirmware

All code written, produced and arranged by Ahmed Zafar

(^^ Do you get the reference?)

© 2026 Ahmed Zafar