Dr. Azhar Imran

Beijing University of Technology, China.

BIO: Dr. Azhar Imran is an Associate Professor at the Department of Computer Science, Beijing University of Technology, China. With over 13 years of academic experience, he specializes in Artificial Intelligence, Data Science, and Machine Learning, and has made significant contributions in areas such as Natural Language Processing (NLP), Generative Adversarial Networks (GANs), Computer Vision, and Cyber Intelligence. Dr. Imran has published over 85 research articles and has been invited to deliver keynote speeches at prestigious conferences, including ICBDDM-24, ICCTEC, CCET25, CVIT-24, ICDSP24, and CVIT-23.

As a Senior Member of IEEE, Dr. Imran is also an active member of various academic and professional committees and serves on the editorial boards of multiple high-impact journals. Throughout his career, he has been recognized with several awards, including the Outstanding Graduate Award and Best Researcher Award from Beijing University of Technology, as well as the Embassy Honored Award from the Pakistan Embassy in Beijing.

Dr. Imran’s research continues to bridge the gap between academic advancements and real-world AI applications, particularly in the fields of healthcare and cybersecurity. His work focuses on using AI-driven solutions to enhance systems such as fall detection for elderly care, medical image processing for diagnosis improvement, and cyber intelligence for better security frameworks.

Speech Title: Computational Intelligence in Healthcare: Navigating hope vs hype in China 

Abstract: Computational Intelligence (CI) has emerged as a transformative force in healthcare, promising unprecedented advances in diagnosis, treatment, and personalized medicine. Techniques such as machine learning, deep learning, natural language processing, and evolutionary algorithms are redefining how clinicians interpret medical data and make decisions. However, alongside the optimism lies considerable hype exaggerated claims, ethical concerns, data biases, and limited clinical validation that often hinder real-world impact. This speech, Computational Intelligence in Healthcare: Hope vs. Hype, explores the fine balance between technological promise and practical limitations. It highlights success stories in predictive diagnostics, drug discovery, and medical imaging while critically addressing challenges related to data quality, model interpretability, regulatory compliance, and patient trust. The discussion aims to separate genuine innovation from inflated expectations, urging researchers and policymakers to adopt a responsible, evidence-driven approach to integrating CI into healthcare systems. Ultimately, the talk emphasizes that the true hope of computational intelligence lies not in replacing clinicians but in empowering them through transparent, ethical, and human-centered AI.