Ghulam A.

Key Skills

Software

Other

OpenCV AI Kit (OAK)

Top Subject Matter

Computer vision for online safety (human detection within videos)

Nonprofit information systems and AI/Computer Vision for monitoring and analytics

Top Data Types

Image

Top Task Types

Object Detection

Freelancer Overview

Lead Researcher, Video-Vigil (AI based Web Browser Extension). Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and OpenCV AI Kit (OAK). Education includes Bachelor of Software Engineering, COMSATS University Islamabad (2024) and Diploma of Associate Engineering (DAE), Karakurum Polytechnic Institute (2020). AI-training focus includes data types such as Image and labeling workflows including Object Detection, Computer Programming, and Coding.

Labeling Experience

MIS and Automation Officer, Community Development Foundation Pakistan (CDF)

OpenCV AI Kit (OAK)Image

Developed and maintained AI-powered solutions involving computer vision for image and video analysis, including object detection and automated monitoring systems. Implemented machine learning models for predictive analytics tasks such as anomaly detection and trend forecasting. Built supporting backend components and APIs to operationalize the AI and analytics workflows. • Developed computer vision solutions using Machine Learning, Deep Learning, OpenCV, and YOLO models • Implemented predictive analytics models for anomaly detection and trend forecasting • Automated data extraction, cleaning, transformation, and reporting using Python and SQL • Designed and optimized database structures to support efficient AI/analytics pipelines

2025 - Present

Lead Researcher, Video-Vigil (AI based Web Browser Extension)

OtherImageObject Detection

Built and tested an AI-based real-time human detection module for a browser extension project. The work focused on using an existing Faster R-CNN Inception V2 COCO model as part of the detection pipeline. The output supported detecting violent content in videos by identifying people in frames. • Trained/leveraged Faster R-CNN Inception V2 with COCO configuration for detection • Implemented real-time human detection logic for video frames • Validated detection results to establish a robust framework for later stages • Prepared the system foundation for subsequent violent-content detection modules

2023 - 2024

Education

Work History