Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

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.…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.

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.…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.

Available to hire

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.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

Urdu

Fluent

Work Experience

Machine Learning Engineer at Inoviks Soft Solution

February 1, 2019 - June 3, 2024

Led the development of AI pipelines in computer vision and NLP using state-of-the-art models such as YOLO, Faster R-CNN, U-Net, and Large Language Models. Managed projects including deepfake detection, medical image segmentation, 3D tracking, OCR, and custom RAG-based chatbots. Successfully deployed machine learning models into production environments via Docker and REST APIs using Flask and Django. Utilized cloud platforms like AWS and GCP with Kubernetes container orchestration. Played an active role in cross-functional collaboration, optimizing system performance, and publishing academic research.