Muhammad Mansoor Alam

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Muhammad Mansoor Alam

Hilton Pharma Merit Scholar

Graduate of 2026
BS Computer Science

Aspiration Statement

Final-year Computer Science student with hands-on experience in deep learning, computer vision, and full-stack development. IEEE-published researcher interested in building impactful products in applied AI/CV and software engineering.

Core Skills

  • API Integration/Security Sandboxing
  • C++
  • Fine-Tuning & Transfer Learning
  • Full-Stack Development (React, Node.js, Express)
  • Python AI Model Training

Core Competencies

  • Effective Presentation Skills

Preferred Career Paths

First priority: AI/ML Engineer

Second priority: Software Engineer

Third priority: Data Scientist

Experience

Leadership / Meta-curricular

  • Events Cabinet Member, Habib University Student Government
  • Security Team Lead - Hucon, Multiverse Club
  • Orientation Leader
  • Career Services Ambassador
  • Career Connect Event Manager

Internship / Volunteer Work

  • Cybersecurity Intern, K-Electric (June – August 2025)

Publications / Creative Projects

  • Research Paper – Research paper on "Automating ROP Diagnosis and Severity with Deep Learning", published at IEEE 22nd International Conference on Smart Communities (HONET 2025).

Final Year Project

Project Title

ML-Powered Predictive Fault Management in Power Distribution Systems for K-Electric's Power Grid

Description

My FYP, developed in collaboration with K-Electric, aims to build Karachi's first machine learning-based system for predicting power outages before they occur. The system uses historical fault data, weather patterns, and grid load information to train predictive models that identify high-risk areas and time windows for outages. The goal is to enable proactive maintenance, reduce unplanned downtime, and improve reliability for a grid serving 20 million+ people. Key components include a feature store for structured data pipelines, a Random Forest-based classifier and regressor, and smart retraining logic to keep the model up to date. The project directly addresses a critical infrastructure challenge in Karachi.

Project Pictures