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AI Engineer with 1+ years in Machine Learning & Computer Vision
AI Engineer with hands-on experience in developing and deploying end-to-end Machine Learning and Computer Vision solutions. Currently working at CDGAI, CECOS University Peshawar, I specialize in building production-ready AI systems from data collection and preprocessing to model training, integration, and deployment. Key achievement includes developing a ResNet18-based Flood Detection System using Sentinel-1 SAR imagery, achieving 93.75% validation accuracy and enabling real-time flood monitoring for Peshawar using Google Earth Engine and Streamlit. Proficient in PyTorch, TensorFlow, YOLO, OpenCV, FastAPI, and Streamlit, I am passionate about leveraging AI and Computer Vision to solve real-world problems and deliver impactful, scalable solutions.
CECOS University of Engineering and Technology
Bachelor in Software Engineering
November 1, 2021 – August 1, 2025
Government Superior Science College
FSC · Pre Engineering
August 1, 2019 – July 1, 2021
Army Public School and College System
Matric
March 1, 2008 – May 1, 2019
CDGAI CECOS University Peshawar
AI Engineer
October 1, 2025 – May 1, 2026
Peshawar, Khyber Pakhtunkhwa, Pakistan
NCAI UET Peshawar
Computer Vision Engineer Intern
January 1, 2025 – October 1, 2025
Peshawar, Khyber Pakhtunkhwa, Pakistan
PakAir Sehat Awaz
June 25, 2026 – Present
Developed a fog detection model to estimate visibility percentage. Created an AQI recommendation bot for public safety alerts. Generated advisory recommendations for government portals based on pollution levels.
View ProjectRed Light Violation Detection System
June 25, 2026 – Present
Developed a computer vision model to detect vehicles crossing red lights using frame-by-frame video analysis. Also used OCR for detected number plates and violated car images. Technologies & Libraries: Python, OpenCV, NumPy, Pandas.
View ProjectFlood Detection through SAR images
June 25, 2026 – Present
Developed a ResNet18 based flood detection model using Sentinel-1 SAR imagery with 93.75% validation accuracy. Processed nearly 3,957 SAR acquisitions from the SEN12-FLOOD dataset. Built a live flood monitoring dashboard using Google Earth Engine and Streamlit. Enabled real time flood risk visualization and prediction for Peshawar.
Smart Teacher Evaluation System
June 25, 2026 – Present
Developed an AI-powered smart evaluation system using Deep Learning and NLP to automate subjective answer assessment. Built an end-to-end Machine Learning pipeline including data preprocessing, model training, evaluation, and prediction generation. Applied text processing techniques such as tokenization, embeddings, and semantic similarity analysis for accurate answer scoring. Evaluated model performance using accuracy, precision, recall, and F1-score to improve automated grading reliability.
View ProjectAI-Based Transformer Health Monitoring with Agentic RAG System
June 25, 2026 – Present
Developed an AI based diagnostic system using XGBoost to classify transformer faults from Dissolved Gas Analysis (DGA) data. Built a multi agent RAG framework using LangChain to retrieve and reference maintenance standards from IEEE/IEC documentation. Implemented advanced feature engineering methods including Rogers’ Ratio and Duval Triangle analysis. Deployed the application using FastAPI, Streamlit, and Docker for scalable cloud deployment.
Data Analytics And Business Intelligence
DigiSkills
June 1, 2026 – Present
Data Science and AI Bootcamp
ATOMCAMP
June 1, 2026 – Present
Share Data Through Art of Visualization
Coursera
June 1, 2026 – Present
Python and Statistics For Financial Analysis
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio is diverse, covering environmental monitoring, industrial diagnostics, education, and public safety, which indicates a broad interest in applying AI to various domains. The involvement in university-affiliated AI centers (CDGAI, NCAI) suggests an inclination towards research and practical application. The target role of 'AI Engineer' aligns well with the candidate's demonstrated skills and project focus. The breadth of skills and project types suggests a good cultural fit for an innovative and problem-solving environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to work on diverse applications. The experience in both contract and internship roles suggests adaptability. However, without direct assessment data, it's difficult to fully evaluate communication, teamwork, or stress handling capabilities.