Syed Muhammad Hasan Naqvi

Syed Muhammad Hasan Naqvi

Class of 2018
BS Electrical Engineering

Core Skills

  • Design Research
  • Project Management
  • Cross-functional Collaborations
  • Human-Centered Design
  • Google Sheets
  • Cascading Style Sheets (CSS)
  • Microsoft Office, Microsoft Excel
  • Adobe Illustrator, Adobe InDesign
  • Embedded Systems
  • Python, C++, JavaScript

Academic Awards / Achievements

  • Global Ugrad Exchange Program, Florida Gulf Coast University, Jan 2017 - May 2017
  • Stanford Summer International Honours Program, June 2016 - Aug 2016

Experience

Leadership / Meta-curricular

  • Participant, Big Data Predictive Analysis Workshop, July 2015 - Aug 2015
  • Secretary, HUSC, March 2015 - Jan 2016
  • Vice President, Pi Phi Society, Aug 2015 - March 2016

Internship / Volunteer Work

  • Teaching Assistant, HU Computer Science Department, Aug 2015 - Dec 2015

Final Year Project

Project Title

Automatic Scratch Detection on Vehicle Assembly Line

Description

Precise detection of surface flaws, especially scratches and dents, is a difficult task for human vision. Our capstone design project is on the development of a low-cost system that uses vision algorithms to accurately identify scratches on a vehicle assembly line. The system can account for defects with random shapes, low contrast or that are obscured by the natural texture of the surface, whereas a robotic arm allows for movement of the camera system. A multi imaging setup allows to predict the exact source of the scratch. This work is being done in partnership with a local car manufacturing company and will help them add automated tools on their assembly line. This is a joint project with Saira Khan and Muhammad Ashir Wahid.

Project Pictures