Prof. 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.

Prof. Pietro S. Oliveto

Southern University of Science and Technology, China

BIO: 

Pietro Oliveto received the Laurea degree and PhD degree in computer science respectively from the University of Catania, Italy in 2005 and from the University of Birmingham, UK in 2009. He has been EPSRC PhD+ Fellow (2009-2010) and EPSRC Postdoctoral Fellow (2010-2013) at the University of Birmingham, UK and Vice-Chancellor's Fellow (2013-2016) and EPSRC Early Career Fellow (2015-2020) at the University of Sheffield, UK. Before moving to SUSTech he was Chair in Algorithms at the Department of Computer Science, University of Sheffield, UK.

His main research interest is the performance analysis, in particular the time complexity, of bio-inspired computation techniques including evolutionary algorithms, genetic programming, artificial immune systems, hyper-heuristics and algorithm configuration. He is currently building a Theory of Artificial Intelligence Lab at SUSTech.

He has guest-edited journal special issues of Computer Science and Technology, Evolutionary Computation, Theoretical Computer Science, IEEE Transactions on Evolutionary Computation and Algorithmica. He has co-Chaired the IEEE symposium on Foundations of Computational Intelligence (FOCI) from 2015 to 2021 and has been co-program Chair of the ACM Conference on Foundations of Genetic Algorithms (FOGA 2021) and Theory Track co-chair at GECCO 2022 and GECCO 2023. He is part of the Steering Committee of the annual workshop on Theory of Randomized Search Heuristics (ThRaSH), was Leader of the Benchmarking Working Group of the COST Action ImAppNIO, is member of the EPSRC Peer Review College and is Associate Editor of IEEE Transactions on Evolutionary Computation.

Speech Title: To be Updated

Abstract: To be Updated