Muhammad Faiq Qazi

PROFESSIONAL PROFILE Software engineer from NUST EDUCATION Software Engineering SEECS , Islamabad , 2.96 (2022) INTERNSHIP EXPERIENCE Shhadiyana 06-Jun-2024 - 06-Oct-2024 • Developed responsive user interfaces using Figma, React.js, and Next.js, while implementing backend functionality and Schema implementation with Express.js and PostgreSQL, through robust RESTful APIs. • Worked on mobile application for Shadiyana Solutions using React Native, integrating frontend and backend features in existing code along with Firebase chat and image storage in S3 bucket. • Migration of the website’s deployment from AWS Elastic Beanstalk to a containerized solution using Amazon ECS and ECR, implementing Terraform for efficient infrastructure management and version control. Funavry technologies 06-Jun-2025 - 19-Sep-2025 Worked on a multi-agent AI system, with primary responsibility for integrating Google services including Google Docs, Forms, Sheets, and Meet into the agentic workflow. Conducted feasibility and cost analysis research for cloud infrastructure and third-party billing services, supporting informed technology decisions for ongoing projects. Explored and evaluated emerging AI technologies, including workflow automation platforms (n8n) and voice-based agentic platforms such as Retell and Eleven Labs FINAL YEAR PROJECT Explainable AI For EEG epileptic disorders (NeuroXplain) NeuroXplain is an explainable AI framework designed to make EEG-based neurological disorder classification transparent, interpretable, and clinically meaningful. It combines deep learning models (such as CNNs or Transformers) with state-of-the-art explainability techniques including SHAP, LIME, Grad-CAM, and Integrated Gradients to reveal which EEG channels, time windows, and frequency bands drive model decisions. By grounding predictions in neurophysiological evidence and visual explanations, NeuroXplain aims to bridge the gap between high-performance EEG classifiers and clinician trust, enabling reliable analysis of disorders using datasets like TUH EEG, CHB-MIT, and Bonn EEG. TECHNICAL EXPERTISE Experience Upwork Freelancer (Computer Vision & LLM Engineering) Oct 2024– Present Remote • Specialized in delivering computer vision and large language model (LLM) solutions for diverse client requirements. • Designed and developed end-to-end AI systems, providing customized machine learning solutions tailored to ...

Software engineer from NUST