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Schedule Interview NowMy name is Aneeba A. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Machine Learning, Computer Vision, TensorFlow, Deep Learning, PyTorch, etc.. I hold a degree in Bachelor of Science (BS), Master's degree. Some of the notable projects I’ve worked on include: AI Cybersecurity Automation Agent - n8n Workflow System, Urban Vehicular Emissions Detection using YOLOv5x and YOLOv8m, Intelligent Q&A Platform with Gemini API for Summarized Responses, Email Classifier Using n8n and AI Models for Automated Categorization, Mobile Inventory Management System with AI and Airtable Integration, etc.. I am based in Islamabad, Pakistan. I've successfully completed 11 projects while developing at Softaims.
I value a collaborative environment where shared knowledge leads to superior outcomes. I actively mentor junior team members, conduct thorough quality reviews, and champion engineering best practices across the team. I believe that the quality of the final product is a direct reflection of the team's cohesion and skill.
My experience at Softaims has refined my ability to effectively communicate complex technical concepts to non-technical stakeholders, ensuring project alignment from the outset. I am a strong believer in transparent processes and iterative delivery.
My main objective is to foster a culture of quality and accountability. I am motivated to contribute my expertise to projects that require not just technical skill, but also strong organizational and leadership abilities to succeed.
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Systems Limited
Built an intelligent cybersecurity automation system using n8n that processes real-time threat intelligence feeds and automates incident response. The system analyzes malicious IP addresses, calculates risk scores using multi-factor algorithms, and automatically executes blocking, alerting, or monitoring actions based on threat severity. Features include email/Slack notifications, comprehensive security reporting, and production-ready error handling. Successfully processes 25+ threats per execution with 95%+ accuracy, reducing manual SOC workload.
Goal: Detect smoke-emitting vehicles in cities to support environmental regulations. Solution: - Used YOLOv5x (SGD) & YOLOv8m (Adam) on 4K+ augmented images. - Preprocessing: resize & normalize. Impact: Enables scalable emissions monitoring, aiding policymakers & reducing urban air pollution.
Goal: Create an intelligent Q&A tool to deliver concise, accurate answers and aid in exam preparation. Solution: Used Gemini API to summarize backend data, query databases, and provide context-aware responses with helpful resource links. Impact: Reduced research time, improved accuracy, and enhanced learning efficiency.
Developed an email classification system using n8n, integrating Gemini's chat model and Message-A model. The system automatically categorizes incoming emails and saves them as draft emails for further action, streamlining email management and reducing manual work.
Built a mobile inventory management system using n8n, integrating the Gemini model for intelligent decision-making. The system stores memory in n8n and links to Airtable for real-time inventory tracking, enhancing efficiency and data accuracy.
Bachelor of Science (BS) in Mathematics & Data Science
Master's degree in Computational Sciences and Engineering (AI)