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Schedule Interview NowMy name is M Raffay A. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Robotics, Artificial Intelligence, Machine Learning, Deep Learning, Reinforcement Learning, etc.. I hold a degree in . Some of the notable projects I've worked on include: Real-Time Multi-Object Tracking and Anomaly Detection in Warehouses, AI-Powered Crop Monitoring and Yield Prediction System, Smart Greenhouse Monitoring System Using ESP8266 and Linux, Soccer and Service Robots, Plant disease classification with React app, etc.. I am based in Lahore, Pakistan. I've successfully completed 10 projects while developing at Softaims.
I employ a methodical and structured approach to solution development, prioritizing deep domain understanding before execution. I excel at systems analysis, creating precise technical specifications, and ensuring that the final solution perfectly maps to the complex business logic it is meant to serve.
My tenure at Softaims has reinforced the importance of careful planning and risk mitigation. I am skilled at breaking down massive, ambiguous problems into manageable, iterative development tasks, ensuring consistent progress and predictable delivery schedules.
I strive for clarity and simplicity in both my technical outputs and my communication. I believe that the most powerful solutions are often the simplest ones, and I am committed to finding those elegant answers for our clients.
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Ventrazil
Created a system to track forklifts, pallets, and workers in large warehouse environments in real-time. Implemented anomaly detection for unauthorized access, unsafe practices, or equipment malfunctio
Developed a system using satellite/drone imagery to monitor crop health, detect diseases, and predict yield. Include features like: Identifying areas of potential pest infestations using multispectra
This IoT-based project leverages the ESP8266 Wi-Fi module and a Linux server (Raspberry Pi/Rock Pi) to monitor and control greenhouse conditions remotely. Sensors for temperature, humidity, soil moist
The project developed a responsive testbed for soccer-playing robots using an Off-field Computer (OFC) and a global vision system. Robots were tracked via color-based image processing, and a PID contr
• Developed a plant disease classification app using Kaggle data and React, solving the problem of accurately diagnosing plant diseases for crop management. • Trained a 99.2% accurate deep learning mo
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2020-01-01-2024-01-01