Syed Muhammad Kazim Raza Rizvi
Core Skills
- Agile Methodologies
- Cross-functional Team Leadership
- Networking
- Data Analysis
- Content Management
- Analytical Skills
- Python
- Microsoft Office
- Research and Development (R&D)
- Figma
- WordPress
- Adobe Premiere Pro, Adobe Photoshop, Adobe Illustrator
- Design Thinking
Academic Awards / Achievements
- Best Design Award, Design Intensive Workshop, Aug 2017
Experience
Leadership / Meta-curricular
- Member, Physics Astronomy Club, Aug 2014 - Dec 2017
- ‘Chalo Choro’, Published work in Kashf magazine, Jan 2018
- Senator, HU Student Government, Jan 2017 - Jan 2018
- Chair, Student Ethos Committee (HUSG), Jan 2017 - Oct 2017
- Founder and President, HU Mathematics Symposium, Nov 2016
Final Year Project
Project Title
Crack Identification of Concrete Surfaces Using Convolution Neural Networks
Description
Automation is one of the rapidly emerging fields of research in the contemporary context. Our capstone design project is about automating the process of crack identification on roads. The algorithm works on convolution neural networks which is a part of deep (machine) learning. Crack detection on long patches of road proves to be a challenge if done manually. To counter this problem, we have developed a specialized rover that can navigate through large distances while acquiring images of the road. These images are then fed to our central processing system that can identify cracks of different shapes, depth and length. Through GPS tagging, exact location of the cracks can be provided to the maintenance crew. This is a joint project with Sakina Maskawala and Ambreen Aslam.