Mr. Ahmad Muhammad | Medical Image Analysis | Best Researcher Award

Muhammad Ahmad is a passionate AI researcher and software engineer currently pursuing a Master’s in Information and Communication Engineering at the University of Electronic Science and Technology of China (UESTC). With a Bachelor’s in Computer Science from the University of South Asia, Lahore, he has gained extensive experience in generative AI, LLMs, deep learning, and medical image analysis. He has served as a Software Engineer at E-teleQuote Inc. (USA), where he led projects involving LLaMA 3.1, sentiment analysis, and real-time chatbot systems. His academic contributions include first-author publications on Alzheimer’s disease and brain tumor diagnosis using hybrid deep learning models. Recognized with multiple awards and scholarships, including a fully funded Master’s scholarship, Ahmad brings together strong programming skills, leadership experience, and a commitment to innovation in healthcare AI. His work reflects a deep interest in combining machine learning with medical imaging to solve real-world challenges through intelligent systems.

Profile

• Orcid

🎓 Education

Muhammad Ahmad holds a Master’s degree in Information and Communication Engineering from UESTC, Chengdu, China, where he maintains a GPA of 3.54/4.0 and focuses on generative AI, LLMs, deep learning, and medical image analysis. Previously, he earned a BS in Computer Science from the University of South Asia, Lahore, Pakistan, graduating with a CGPA of 3.16/4.0. His final year project—Walmart Weekly Sales Prediction—reflected his early commitment to machine learning. His academic journey has been bolstered by self-motivated learning, with certifications from Stanford University, IBM, and DeepLearning.AI in TensorFlow, machine learning with Python, and data analysis. Alongside his formal education, Ahmad has organized machine learning workshops and led ACM and IEEE student chapters, showcasing a combination of technical proficiency and community leadership. His educational background lays a strong foundation for interdisciplinary AI research, especially in biomedical applications.

🧪 Experience

Muhammad Ahmad has valuable industry experience as a Software Engineer in AI at E-teleQuote Inc. (Florida, USA), where he led projects utilizing LLaMA 3.1 for document processing and chatbot development. He developed robust NLP solutions, including sentiment analysis and speech recognition systems, while deploying and optimizing AI models for production environments. Earlier, during his internship at Quid Sol (Lahore), he worked on deep learning-based object detection, segmentation, and noise reduction, applying feature engineering and model optimization techniques. Beyond technical roles, he held leadership positions, including Vice-Chair of the ACM Society and event organizer for IEEE, fostering innovation within academic communities. Ahmad’s experience combines hands-on coding with strategic project leadership in AI, making him adept at translating theoretical machine learning concepts into real-world applications, particularly in healthcare and image analysis domains.

🏅 Awards and Honors

Muhammad Ahmad’s academic excellence and leadership have earned him multiple awards. He received a fully funded scholarship from the University of Electronic Science and Technology of China (UESTC) to pursue his Master’s studies in AI. In 2020, he was awarded a semester scholarship for conducting a high-impact workshop on machine learning at the University of South Asia. His community engagement was recognized by the Rooh Foundation and the Government of Pakistan for volunteer work with the Humanity Welfare Foundation. In technical competitions, he secured 1st place at COMSATS University’s Web Development Competition (April 2018) and 2nd place at Superior University (September 2018), demonstrating his early programming excellence. Additionally, Ahmad has earned respected certifications in machine learning, deep learning, and data analysis from Stanford, IBM, and CognitiveClass.ai, highlighting his continuous pursuit of technical mastery in the field of artificial intelligence and data science.

🔬 Research Focus

Muhammad Ahmad’s research focuses on deep learning, generative AI, and large language models (LLMs), particularly applied to medical image analysis. He is committed to enhancing diagnostic accuracy in complex medical conditions using AI. His notable work includes developing a hybrid deep learning architecture with adaptive feature fusion for multi-stage Alzheimer’s disease classification, published in Brain Sciences. Another study, submitted to the International Journal of Machine Learning and Cybernetics, proposes a dynamic fusion model for brain tumor diagnosis. His academic pursuits aim to integrate LLMs and computer vision for robust, intelligent medical systems. Ahmad’s goal is to bridge gaps between artificial intelligence and clinical practice, focusing on real-time, explainable, and scalable AI systems for healthcare. His research embodies a combination of theoretical rigor and practical implementation, striving to deliver solutions that are both impactful and clinically relevant.

✅ Conclusion