Mubashir Anees

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Mubashir Anees

Hilton Pharma HU TOPS Scholar

Graduate of 2026
BS Computer Engineering

Aspiration Statement

Driven by AI's role in modern industry and security, I aim to be an AI Engineer. I combine research experience with full-stack skills in React and Django to build impactful solutions.

Core Skills

  • AWS
  • C++
  • CSS
  • Docker
  • Git
  • HTML
  • Javascript (React)
  • Kubernetes
  • Python

Core Competencies

  • Acts with Ownership
  • Adaptability
  • Planning
  • Takes Initiative

Preferred Career Paths

First priority: AI Engineer

Second priority: Web Development

Third priority: Data Engineer/IT Engineer

Experience

Leadership / Meta-curricular

  • General Secretary, Moseequi & Raqs
  • Deputy Director General Humun Viii, Vii & Vi, Gaming Club Habib Debate Union
  • Sindhi Lead, Arts and Culture Club
  • Graduation Committee Member, Habib University Student Government
  • Photography Team Member for Hucon, Multiverse Club

Internship / Volunteer Work

  • Undergraduate Researcher, Habib University (June – August 2025)
  • Undergraduate Researcher, Habib University (June – August 2024)

Publications / Creative Projects

  • Research Paper – Research Paper on "Deployment-Oriented Memory-Based Visual Inspection of Injection-Molded Parts" Published in Springer CVC 2026

Final Year Project

Project Title

Aesthetic Fault Detection of Injection Molded Parts

Description

The Aesthetic Fault Detection (AFD) project is an automated quality control solution developed for Dawlance to inspect large injection-molded parts. It replaces subjective manual inspection, which causes over PKR 6 million in annual losses, with an objective, high-precision AI system. Core Technology Hardware: A custom Split-Axis mechanical system (turntable and rotating arm) captures 360-degree views of components up to 100x70x50 cm. Software: The PatchCore unsupervised deep learning algorithm identifies subtle surface defects (scratches, dents) by learning from "perfect" samples, bypassing the need for rare faulty data. Key Outcomes Efficiency: Delivers results within a 3-minute production cycle with up to 98% accuracy. Viability: Offers a 9-month ROI while advancing SDG 9 and 12 through waste reduction.

Project Pictures