Shahmir Mustafa Chaudhry

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Shahmir Mustafa Chaudhry

Graduate of 2026
BS Electrical Engineering

Aspiration Statement

My interests lie in research and development in the domain of medical imaging: leveraging AI for effective diagnostics, improving acquisition methods, and identifying patterns across diseases to improve prognosis.

Core Skills

  • Data Science
  • Image Processing
  • Python
  • Signal Processing
  • Deep Learning

Preferred Career Paths

First priority: Computer Vision Engineer

Second priority: Research Scientist

Third priority: N/A

Experience

Leadership / Meta-curricular

  • Student Ambassador
  • Vice President, Ieee (Institute of Electrical and Electronics Engineers)
  • Basketball Team Member, Sports & Recreational Club

Internship / Volunteer Work

  • Computer Vision Engineer, Lambda Theta (March – May 2026)
  • Teaching Assistant, Habib University (January 2024 – April 2026)
  • Intern, HBL Bank Limited (December 2024 – January 2025)
  • Design Engineer, Data Essentials (May 2023 – January 2024)

Publications / Creative Projects

  • Research Paper – "Biosensing-Driven Framework for Assistive Therapy: A Proof-of-Concept Study" published in IEEE Xplore
  • Research Paper – "HU at SemEval Task 10: Psycholinguistic Extraction and Classification for Conspiracy Narratives" published at ACL 2026
  • Exchange Program – Berkeley Learn Abroad Semester (Fully Funded)

Final Year Project

Project Title

A Gamified Physiotherapy Ecosystem

Description

Rehabilitation is a critical component of recovery for individuals with injuries, neurological disorders, or post-surgical conditions. However, traditional rehabilitation methods often suffer from low patient engagement, resulting in reduced adherence and slower recovery. This project introduces a gamified rehabilitation platform designed to enhance motivation and provide real-time progress tracking through advanced 3D motion capture and biofeedback technologies. Utilizing deep learning models for pose estimation (MediaPipe) integrated with RGB-D depth sensor cameras (e.g., Intel RealSense) for true real-world metric tracking, the platform precisely assesses key physical movements.

Project Pictures