|
Generative AI in Scholarly Publishing: Ethical, Practical, and Policy Perspectives
March 27, 2025
11:00 am - 12:00 pm ET
This webinar is sponsored by Digital Science.
This webinar will feature four compelling speakers with expertise in scientific and clinical research and publishing, scholarly peer review and publications, and supporting AI infrastructure and frameworks in clinical and academic institutional settings. The expert panelists will inform the audience about the evolving use of generative AI in different capacities in the scholarly publishing industry and share actionable and practical insights to responsibly and ethically leverage generative AI and define policies and guidelines to move our industry forward. The discussion will be valuable for authors, researchers, editorial office professionals, peer reviewers, editors, scholarly publishing domain adjacent vendors, publishers, and society professionals.
Speakers
Srija Chakraborty is a Scientist at USRA and specializes in applied machine learning for scientific datasets, currently focusing on satellite observations for Earth and Space Sciences. Her research interests are centered around machine learning for scientific applications, with an emphasis on unsupervised learning, anomaly detection, time-series analysis, and foundation models. She serves on NASA’s Black Marble Science Team leading machine learning efforts and on NASA’s FireSense Implementation Team assisting stakeholders for wildfire management using machine learning. She is also interested in responsible AI, AI Policy and Governance and is currently a Science Policy Fellow with the American Geophysical Union’s Voices for Science program and serves as a working group member and secretary for IEEE Standards Working Group on Environmental Impact of AI. Prior to joining USRA, she was a NASA Postdoctoral Program Fellow at Goddard Space Flight Center and received a Ph.D. in Computer Engineering from Arizona State University in 2019.
George Currie is Content Manager at eLife Sciences Publications. He joined eLife in 2023 to help communicate the need for Open Science and alternative models of publishing. He previously worked at Oxford University Press where he developed Open Access author value propositions, and as Brand Manager at Hindawi where he gained a deep understanding of the systems and challenges in research and research publishing. He cares about fairer systems, research integrity, and public understanding of science.
Jordan Hilsman is a Machine Learning Engineer at Children’s Healthcare of Atlanta, and formerly an AI Research Engineer at the University of Pittsburgh. His research focused on Clinical Natural Language Processing and Ethical Development & Adoption of Generative AI. He works now in ML systems in healthcare, focused on developing and deploying ethical and robust implementations.
Dr. Xuan Wang is an associate professor of information systems from Robert C. Varkar College of Business and Entrepreneurship at the University of Texas Rio Grande Valley. She received her doctoral degree in information systems and decision sciences from Louisiana State University. Her research focuses on causal inference, Artificial Intelligence, and advanced methodological applications. Her publications have appeared in journals in the areas of information systems and decision science, such as Information Technology & People, Information Systems Frontiers, Internet Research, Computers & Security, AIS Transactions on Human-Computer Interaction, and many other journals and major information systems conferences.
Moderator: Chhavi Chauhan
|
