About
Aspiring AI & Machine Learning graduate with a strong foundation in Python, SQL, and data manipulation using Pandas, along with hands-on experience in data analysis and visualization using Power BI. Knowledgeable in Manual Software Testing, including test case design, defect tracking, bug reporting, and software quality assurance methodologies. Familiar with Automation Testing concepts and tools, with an understanding of test scripting and workflow validation. Skilled in API Testing using Postman, including request validation, response analysis, and endpoint testing. Passionate about solving real-world problems through data-driven and quality-focused approaches, with strong analytical, problem-solving, and attention-to-detail skills. Actively seeking entry-level opportunities to apply and expand technical expertise in AI/ML and Software Testing.
Skills & Expertise (19)
Work Experience
QA/Software Testing Intern
QSpiders
Feb 2026 - Jul 2026
Performed manual testing on live applications, designing and executing test cases to identify functional defects. Built automation test scripts using Playwright to validate UI workflows and reduce manual regression effort. Wrote and executed SQL queries to validate backend data integrity. Tested REST APIs for functional accuracy, logging and tracking defects to resolution.
Major Project
AI-Driven Smart Home Automation with IoT and NLP
Jan 2025 - Dec 2025
Built an AI-powered home automation system integrating IoT and NLP to enable voice- and sensor-based control of appliances, lighting, and safety systems for smart home environments. Designed a voice-controlled automation architecture using Google Assistant and Dialogflow, enabling hands-free appliance control and real-time natural language command interpretation. Engineered an ESP32-based embedded system integrating 6 sensor types (temperature, motion, gas, flame, light, ultrasonic) to enable real-time environmental monitoring and automated decision-making. Built cloud-connected communication using Firebase and MQTT protocols, enabling live sensor visualisation and instant alert notifications through the Blynk IoT dashboard for remote device management. Implemented automated safety and convenience workflows — including gas leak detection, fire/intrusion alerts, and motion-based lighting — to improve home security and energy efficiency. Applied secure API-based communication between embedded devices and cloud services to ensure reliable and consistent data transmission across the system.
Mini Project
Colour detection using Python & OpenCV
Jul 2024 - Sep 2024
Built a real-time colour detection application using computer vision techniques to identify and classify colours from digital images. Implemented RGB extraction, colour thresholding, and minimum-distance algorithms to classify colours from image data using Python and OpenCV accurately. Designed an interactive UI with mouse-event handling, enabling users to select any pixel and instantly view its corresponding RGB values. Managed structured colour datasets through CSV files, using Pandas for efficient data handling, lookup, and manipulation. Built real-time visualisation features — dynamic text overlay and live RGB display — to improve usability and interaction feedback. Debugged and optimised the image-processing pipeline to improve detection accuracy and application responsiveness.
Education
Bachelor of Engineering in Artificial Intelligence and Machine Learning Engineering - KNS Institute of Technology, Visvesvaraya Technological University
- 2026 · Afghanistan
Certifications
Quality Analyst
Qspiders · 2026
Data Analytics & Visualization - Virtual Job Simulation
Accenture (Forage) · 2024
Software Engineering - Virtual Job Simulation
JPMorgan Chase & Co. (Forage) · 2024
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Skills (19)
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