How AI is reshaping research and publishing

Tracey Brown OBE is the director of Sense about Science. Under her leadership, the charity has launched important initiatives to promote open discussions of evidence, including Risk know-how and AllTrials - a global campaign for the reporting of all clinical trial outcomes. She initiated Evidence Week in the UK Parliament and co-founded the international Maddox prize. Tracey writes about the public and evidence, and leads Sense about Science’s work on transparency of evidence and AI in policy. She is honorary Professor in the Department of Science, Technology and Engineering in Public Policy at UCL. 

Xiaoling Kang is Director of Global Strategic Networks at Elsevier, focusing on China market. She engages and establishes strategic partnership with key academic and governmental stakeholders who share a passion for improving research performance, broadening access to research information and knowledge, and ensuring science delivers positive impacts on society. She plays a leading role in advancing initiatives and use of data analytics to address societal challenges in the areas of sustainability, diversity & inclusion and open science.

Dr. Min Zhang is a Full Professor in the Dept of Computer Sci. & Tech. (DCST), Tsinghua University. She is the director of the AI Institute of DCST, a distinguished member of ACM and CCF, the SIGIR Academy fellow. She specializes in Web search, recommendation, and user modeling. She has been the Editor-in-Chief of ACM Transactions on Information Systems (TOIS) since 2020, and also serves as the General co-Chair of TheWebConf’27, ACM MM’25, and PC co-Chairs of SIGIR’26, RecSys’23, CIKM’23, WSDM’17, etc. She won the “Test-of-Time” award at SIGIR’24, WSDM’22 Best Paper award, IBM Global Faculty Award, etc. She also has long-term industrial cooperations such as Kuaishou, Meituan, Tencent, ByteDance, China Mobile, and more.

Dr. Guanjin (Brenda) Wang is an Associate Professor in Artificial Intelligence at Murdoch University, Perth, Australia. Her research focuses on explainable and responsible AI and multimodal learning, with applications across health and other interdisciplinary domains. Her research has been supported by a range of national and international funding bodies, including Google Research, the Australian Government’s MRFF, ARC, the Western Australian Government’s Future Health Research and Innovation Fund, Healthway Research, and the German DAAD. She is a recipient of both the Google Inclusion Research Award and the Google Academic Research Award. She is particularly interested in how AI can be developed and used responsibly to support research, decision-making, and real-world impact.