Qian Liu is a distinguished researcher from Southwest Jiaotong University, specializing in machine learning and large-scale data analytics. He has conducted extensive research in advanced data mining algorithms, with particular emphasis on graph neural networks and their applications in complex systems. His research has been published in numerous international journals and widely presented at leading data science conferences. Qian Liu is dedicated to advancing the field of data mining through both theoretical innovations and practical applications. His contributions have significantly influenced the development of scalable data mining techniques for big data environments, making him a leading voice in the intersection of machine learning and knowledge discovery.

Dr. Ao Cao is an accomplished researcher from Southwest Jiaotong University, specializing in knowledge discovery and pattern recognition. His work focuses on developing innovative algorithms for extracting meaningful patterns from large-scale datasets, with extensive experience in temporal data mining and causal inference. Dr. Cao has published multiple academic articles in top-tier data mining journals and has been actively involved in the research and implementation of various industrial data mining projects. His interdisciplinary approach combines statistical methods with machine learning techniques, contributing to the advancement of interpretable and actionable knowledge discovery. His research has been instrumental in developing new frameworks for understanding complex data relationships in domains ranging from financial analytics to healthcare informatics.

Associate Professor Yifei Yin is a leading expert in privacy-preserving data mining and federated learning systems. He specializes in developing secure and efficient algorithms that enable collaborative data analysis while maintaining data privacy. He has published numerous academic papers in the field of differential privacy and secure multi-party computation, and has participated in the development of multiple industry standards for privacy-preserving analytics. His contributions have been vital in advancing the practical deployment of privacy-aware data mining solutions. Professor Yin's efforts have received widespread recognition for his emphasis on balancing data utility with privacy protection, enabling organizations to derive insights from sensitive data while complying with privacy regulations and ethical standards.