About Mark: Mark Gahegan is professor of computer science at the University of Auckland, New Zealand, and Director of the university’s Centre for eResearch—a group that is dedicated to improving research outcomes & processes using new computational methods. Prior to this, he was a professor at Penn State University, USA. His research interests are in data science, AI, eScience, computational semantics, information visualization, geographic information science, remote sensing and the philosophy of science. He has written over 150 peer-reviewed articles, given over 150 invited talks, and is PI or Co-PI on about 40 funded projects. He serves on the editorial board of 7 international journals. Mark also directs one of the three large data science platforms in New Zealand (‘Beyond Prediction…’) funded via the NZ Strategic Science Investment Fund.

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An essential part of the bridge are discussion sessions. During the second edition, the community will discuss the following research questions:

• How can AI be effectively used in scholarly communication? This question aims to explore the potential of AI to support scholarly communication activities in different research domains (including, but not limited to computer science, economic, health, physics, law, etc.) such as literature discovery, knowledge synthesis, peer review, etc. while improving efficiency and accessibility.

• Which tools should be used for which purpose? This question aims at mapping existing AI-based tools (e.g., literature search and discovery, writing assistance, fact-checking, bibliometrics) to their appropriate scholarly communication tasks.

• What methodologies, methods, and tools are being developed for AI in scholarly communication? This question aims at comparing approaches across disciplines, identifying best practices, and evaluating the robustness, reproducibility, and scalability of AI systems.

• Which ethical questions must be addressed to avoid misuse of AI in scholarly communication?

For reference, please see a paper written by last year's workshop participants Charting the Future of Scholarly Knowledge with AI: A Community Perspective. Azanzi Jiomekong, Hande Küçük McGinty, Keith G. Mills, Allard Oelen, Enayat Rajabi, Harry McElroy, Antrea Christou, Anmol Saini, Janice Anta Zebaze, Hannah Kim, Anna M. Jacyszyn, Sören Auer. arXiv preprint arXiv:2509.02581. 2025 Aug 27. https://doi.org/10.48550/arXiv.2509.02581

• Hamed Babaei Giglou, TIB - Leibniz Information Centre for Science and Technology and University Library, Hannover, Germany

• Fatemeh Bagheri, Saint Mary University, Halifax, Nova Scotia, Canada

• Hossein Beygi Nasrabadi, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure, Eggenstein-Leopoldshafen, Germany

• Antrea Christou, Department of Engineering and Computer Science, Wright State University, USA

• Aryan Dalal, Kansas State University, Manhattan, Kansas, USA

• Daniil Dobriy, Vienna University of Economics and Business, Austria

• Mark Gahegan, University of Auckland, New Zealand

• Hassan Hussein, TIB - Leibniz Information Centre for Science and Technology and University Library, Hannover, Germany

• Kathleen Jagodnik, Kansas State University, Manhattan, Kansas, USA + Harvard University, USA

• Lena John, TIB - Leibniz Information Centre for Science and Technology and University Library, Hannover, Germany

• Petr Knoth, Knowledge Media institute, The Open University, UK

• Fabian Kovac, Department of Computer Science & Security, University of Applied Sciences St. Pölten, Austria

• Yigit Küçük, Collaborative Drug Discovery, USA

• Enrico Motta, KMi, The Open University, Milton Keynes, UK

• Ebrahim Norouzi, FIZ Karlsruhe - Leibniz Institute for Information Infrastructure, Eggenstein-Leopoldshafen, Germany

• Anmol Saini, Department of Engineering and Computer Science, Wright State University, USA

• Cogan Shimizu, Department of Engineering and Computer Science, Wright State University, USA

• Sanju Tiwari, Sharda University, Greater Noida, Delhi NCR, India