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Sher Ali
CRESCENT STEEL HU TOPS Scholar
Aspiration Statement
I like to work at the intersection of Artificial Intelligence, software systems, and computer engineering, focusing on building reliable, research-driven solutions that scale from theory to practice.
Core Skills
- AI Development
- Computer Vision
- Product Development
- Robotics
Core Competencies
- Acts with Ownership
- Effective Presentation Skills
- Planning
- Takes Initiative
Preferred Career Paths
First priority: AI/ML, Computer Vison Engineer
Second priority: Software Engineer
Third priority: Robotics and Product Design
Experience
Leadership / Meta-curricular
- Executive Member - Treasurer, Entrepreneurship Club
- Event Cabinet Member, Habib University Student Government
- Outreach Member, Serve Club
- Cabinet Member, Gaming Club Habib Debate Union
- Lead - Robotics Competition, IEEE (Institute of Electrical and Electronics Engineers)
Internship / Volunteer Work
- Software Engineer - AI (FYP Contract), Dawlance Arcelik, Pakistan (August 2025 – March 2026)
- Ai Engineer Intern - Remote, Asf Tech Partners (Pvt Ltd), Singapore (June – August 2025)
- Computer Vision Engineer Intern, Agha Khan University Hospital (July – August 2025)
- Summer Tech Researcher, Habib University - Research Department (May 2025 – July 2026)
Publications / Creative Projects
- Research Paper – Research paper on "Enhancing Campus Safety Education Through Immersive Learning: A Constructivist Approach to VR Evacuation Training."
- Competition – Participant of "Invent for Planet" Hosted by Texas A&M University
Final Year Project
Project Title
Collaborative Human-Robot Gantry System
Description
The project aims to eliminate severe musculoskeletal risks at Dawlance by automating the heavy lifting of 40kg microwaves. By transitioning from manual labor to a Human-Robot Collaborative setup, we protect workers from injury while they handle dexterous tasks like quality checks. I am developing a 4-axis gantry robot integrated with a ROS2-based computer vision pipeline on a Jetson Orin Nano. This allows the system to autonomously localize and palletize units within a 3.5m x 3.5m footprint, compliant with ISO 15066 safety standards. The system reduces the NIOSH Lifting Index from a dangerous 3.1 to a safe 1.0, effectively preventing chronic worker injuries. It also minimizes product damage and provides a cost-effective, locally engineered automation solution.
Project Pictures
