**About the Editors**

#### **Xiang Zhang**

Xiang Zhang is an Assistant Professor in the Department of Computer Science at the University of North Carolina (UNC) at Charlotte. Zhang is serving as director of the Charlotte Machine Learning Lab (CML), which boasts around 40 members, including esteemed professors and PhD candidates renowned for their expertise across diverse domains such as deep learning theory, computer vision, natural language processing, reinforcement learning, and time series analysis. Before joining UNC Charlotte, he was a postdoctoral fellow at Harvard University from March 2020 to July 2022. Zhang received his Ph.D. degree (in 2020) in Computer Science from the University of New South Wales (UNSW). His research interests lie in data mining and machine learning with applications in medical time series, brain–computer interfaces (BCIs), and pervasive healthcare. Zhang's research outcomes have been published in prestigious conferences (such as ICLR, NeurIPS, and KDD) and journals (like Nature Computational Science).

#### **Xiaoxiao Li**

Dr. Xiaoxiao Li is an Assistant Professor in the Electrical and Computer Engineering Department at the University of British Columbia (UBC), leading the Trusted and Efficient AI (TEA) Group, and an Adjunct Assistant Professor at the School of Medicine at Yale University. Dr. Li specializes in the interdisciplinary field of deep learning and biomedical data analysis. Her primary mission is to make AI more reliable, especially when it comes to sensitive areas like healthcare. At the TEA Group, they explore a wide range of topics from fundamental machine learning to more focused healthcare-driven AI solutions. The group delves into topics such as learning from multimodal and heterogeneous data, efficient AI models, federated learning, and creating AI models that not only perform tasks but can also be trustworthy. Some of their groundbreaking work includes AI-driven analysis of neuroimages, pathology slides, molecular and clinical notes. In essence, Dr. Li's work is all about bridging the world of advanced machine learning with the practical needs of the healthcare industry.
