Muhammad Midhat

I am Muhammad Midhat, a passionate Machine Learning and Computer Vision Engineer with over 7 years of experience in developing AI-powered solutions across Computer Vision, Natural Language Processing, and Generative AI domains. I hold a Bachelor of Science degree in Computer Science from Government College University Faisalabad (2013–2017), and I’m currently pursuing a Master of Science in Computing (2024–2026) from Universiti Malaysia Pahang, Malaysia. My thesis, titled “Time Series Forecasting for Industrial Machine Logs Data Using LLMs,” has been successfully defended, and I am now fully available for onsite or remote roles, globally. My professional journey includes over 5 years at Inoviks Soft Solution, where I led impactful projects involving 3D object detection and tracking, medical image segmentation, pose analysis, OCR systems, RAG-based chatbots, and LLM integration. Before that, I worked as a C# Developer at Microstarx Software House for 2 years, focusing on desktop application development and database optimization. My technical stack includes Python, C#, PyTorch, TensorFlow, Hugging Face, OpenCV, LangChain, SQL, Docker, and cloud platforms like AWS. I’ve delivered full-cycle ML pipelines—building, deploying, and scaling models into production environments. I’m also actively involved in academic research. I co-authored “Deep Learning-Powered Facial Expression Recognition: Revolutionizing Emotion Detection,” presented at EMSEE 2024, and I’m the first author of a paper submitted to the 2025 IEEE ICSECS conference titled “Literature Review: Time Series Forecasting for Text Data.” With strong hands-on experience, a research-driven mindset, and a deep interest in solving real-world problems using AI, I’m excited to join innovative teams aiming to transform industries with intelligent technology.