Muhammad Ibrahim

AI enthusiast with a solid foundation in data engineering and a keen interest in machine learning model training. Skilled in building data pipelines and preparing datasets for model development. Passionate about leveraging AI to solve real-world problems with hands-on experience in data processing, model deployment, and generative AI.

Adept at working with TensorFlow, PyTorch and Hugging Face ecosystems, with growing exposure to cloud platforms like AWS and a strong focus on building reliable, scalable AI solutions.

AI/ML Engineer - FAST-NUCES

• AI-powered plant disease detection and pest identification system using deep learning and computer vision (OpenCV, TensorFlow), achieving high accuracy across 20+ disease categories.
• Severity analysis module using image segmentation to grade plant health in real time, enabling early intervention and reducing potential crop loss.
• Integrated ML and Generative AI models to generate personalized watering schedules and eco-friendly treatment plans tailored to individual plant profiles.
• Designed an intelligent garden layout planner powered by generative AI, optimizing plant placement based on sunlight, spacing, and compatibility requirements.
• Connected real-time weather APIs to dynamically adjust care recommendations based on live humidity, rainfall, and temperature forecast data.
• Built and deployed scalable RESTful backend APIs using FastAPI with integrated database support for persistent user data and plant health records.

Bachelor of Science - Artificial Intelligence - National University of Computer and Emerging Sciences, Chiniot-Faisalabad Campus (2022-06 - 2026-06)

Intermediate - ICS - KIPS College, Faisalabad (2020-08 - 2022-06)