Muhammad Moiz Masood

PROFESSIONAL PROFILE I am a Computer Science undergraduate graduating in 2026, with core strengths in machine learning, deep learning, large language models, and computer vision. My expertise includes building end to end RAG pipelines, self hosting and deploying LLMs, and developing deep learning based solutions for image segmentation and classification in MRI imaging. I also have strong experience in agentic AI, having built automated outreach systems capable of handling volumes of 1,000+ emails per day. This is complemented by a solid foundation in MLOps and core computer science fundamentals, supported by both research and industry exposure. I have worked as a Research Assistant under the mentorship of Dr. Faisal Shafait at the TUKL Deep Learning Lab, NUST, as well as in industry roles as a machine learning and automation intern, which has given me a balanced perspective on research-driven development and production oriented systems. I am able to work independently with minimal supervision and consistently deliver against tight deadlines. My freelance experience has strengthened my ability to manage both technical and non technical communication with diverse stakeholders. I work effectively in team environments, understand group dynamics, and can identify and leverage individual strengths to contribute toward shared objectives. I have consistently maintained high academic performance with merit-based recognition, and my long term objective is to translate research driven deep learning paradigms into impactful industry applications, particularly within healthcare AI. EDUCATION BS-CS SEECS , Islamabad , 3.61 (2026) INTERNSHIP EXPERIENCE Modern Intelligent Solutions 08-Jul-2025 - 08-Sep-2025 I worked as an Automation Engineer, where I built AI driven workflow automations and scalable outreach systems that significantly reduced manual effort and improved operational efficiency. I worked on cold emailing, cold calling workflows capable of sending 1000+ mails a day. I also had to maintain code repositories regarding these workflows which allowed me to have a hands on experience on how modular, clean is written and maintained TUKL-DLL Nust 04-Jun-2025 - 30-May-2026 I am currently a Research Assistant at the TUKL Deep Learning Lab at NUST, where I work under the mentorship of Dr. Faisal on applied research in cardiovascular MRI for high-field (3T) cardiac CINE imaging. My research focuses on developing deep learning based methods to reduce frequency offset and banding artifacts, with the goal of improving diagnostic reliability. ONT Lab Nust 01-Jul-2024 - 01-Sep-2024 Research intern in ONT Lab NUST where I worked on datasets involving time-series modeling with RNNs, CNNs, transformers, attention mechanisms, and GAN based data augmentation, which strengthened my foundation across a wide range of deep learning paradigms. FINAL YEAR PROJECT

I am a Computer Science undergraduate graduating in 2026, with core strengths in machine learning, deep learning, large language models, and computer vision. My expertise includes building end to end RAG pipelines, self hosting and deploying LLMs, and developing deep learning based solutions for image segmentation and classification in MRI imaging. I also have strong experience in agentic AI, having built automated outreach systems capable of handling volumes of 1,000+ emails per day. This is complemented by a solid foundation in MLOps and core computer science fundamentals, supported by both research and industry exposure. I have worked as a Research Assistant under the mentorship of Dr. Faisal Shafait at the TUKL Deep Learning Lab, NUST, as well as in industry roles as a machine learning and automation intern, which has given me a balanced perspective on research-driven development and production oriented systems. I am able to work independently with minimal supervision and consistently deliver against tight deadlines. My freelance experience has strengthened my ability to manage both technical and non technical communication with diverse stakeholders. I work effectively in team environments, understand group dynamics, and can identify and leverage individual strengths to contribute toward shared objectives. I have consistently maintained high academic performance with merit-based recognition, and my long term objective is to translate research driven deep learning paradigms into impactful industry applications, particularly within healthcare AI.