🎓 Teaching Assistant & AI Researcher

Muhammad Arslan Arshad

Computer Vision • Deep Learning • AI Education

AI researcher and practitioner with hands-on experience in computer vision and image restoration, including scene-text deblurring. Demonstrated expertise in developing hybrid CNN-ViT architectures and real-world research implementations. Actively seeking opportunities to expand into multimodal AI, contributing to cutting-edge research that bridges theory and practical applications in intelligent systems.

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Career Journey

Experience

Academic excellence meets practical innovation

Teaching Assistant

Jan 2025 – Present | UET Lahore
  • Leading lab sessions for Programming Fundamentals and Data Structures courses
  • developed a secure exam system with fullscreen enforcement, tab-switch detection, and comprehensive admin controls. GitHub→
  • Mentoring students in software development and algorithmic thinking

AI Research Intern

Jun 2024 – Sep 2024 | KICS, UET Lahore
  • Conducted research on vehicle classification using deep learning (VGG16/19, ResNet50, ViT)
  • Achieved improved model accuracy through architecture optimization and hyperparameter tuning
  • Developed classification pipeline for color, type, and make recognition

Python & AI Instructor

Oct 2023 – Dec 2023 | APTECH Computer Education
  • Delivered comprehensive 3-month Python & AI curriculum
  • Taught NumPy, Pandas, Matplotlib, and Machine Learning fundamentals
  • Integrated real-world datasets with supervised learning projects
Portfolio

Featured Projects

Research implementations and practical tools

Hybrid CNN-ViT Deblurring

Hybrid CNN-ViT Deblurring Model

Novel architecture combining CNNs and Vision Transformers for restoring motion-blurred scene-text images using the real TextOCR dataset. Demonstrates research-level expertise in computer vision and AI.

TensorFlow CNN ViT OpenCV
GitHub → Paper →
Car Accident Detection

Car Accident Detection

Real-time accident detection system using YOLO for traffic monitoring and emergency response. Highlights applied object detection and real-world computer vision impact.

YOLO Python OpenCV
GitHub → Kaggle Notebook →
Peach Tree Disease Detection

Peach Tree Disease Detection

Computer vision-based system for identifying peach tree diseases from images. Showcases practical application of CNNs for agricultural monitoring and precision farming.

Python CNN OpenCV TensorFlow
GitHub → Kaggle Notebook →
View All Code
Research

Publications

Contributing to the advancement of computer vision

Hybrid CNN-ViT Model for Motion-Blurred Scene-Text Image Deblurring

Under Review – IET Image Processing

A novel approach combining convolutional neural networks with vision transformers to address the challenging problem of motion-blurred text restoration in natural scene images.

Read Preprint on arXiv →
Credentials

Certifications

Continuous learning and professional development

Huawei HCIA – Artificial Intelligence

2024

Industry-recognized certification in AI fundamentals and applications

view Credentials →

NAVTTC – AI & Deep Learning

2023

Comprehensive training in artificial intelligence and deep learning techniques

view Credentials →

Machine Learning Specialization (coursera)

2023–2024
Let's Connect

Contact

Open to collaborations, research opportunities, and discussions

📧

Email

marslan.arshad@uet.edu.pk

LinkedIn

Muhammad Arslan

GitHub

M-ArslanArshad