top of page

Keynote Speakers

iConference invites renowned researchers and scholars to share their vast experience and outstanding achievements. Michael Seadle, Wei Lu, and Sadao Kurohashi give their keynotes at the physical event in Changchun, China.


Michael Seadle will additionally give his keynote at the virtual part of the conference online.

Michael Seadle

Prof. Michael Seadle

iSchools Inc. Executive Director

Humboldt-Universität zu Berlin, Germany

Virtual & On-Site Keynote

Virtual: Monday, 15 April

8am US EAST // 2pm Europe UTC+2 // 8pm China UTC+8

On-Site in Changchun, China: Tuesday, 23 April

10.20 am Local Time

Information Science:
History, Ideas, Applications

People often ask, "What is Information Science?", and the question deserves a clear answer. Information Science is primarily a way of thinking, but explaining the nature of a field typically involves discussing its boundaries. Andrew Abbott explains in the Chaos of Disciplines (2001) why disciplinary boundaries are important. Disciplinary boundaries provide a basis for identity. This is particularly important in academic organisations where that identity determines where a field belongs for administrative purposes. Information Science involves more than the selection or organisation of a particular kind of information. It involves choices about how to process and use the information, and choices about how to store and gather the information. Information Science is a way of thinking that cuts across the boundaries that constrain choices, much like classical fields such as history or philosophy. Language matters as the primary vehicle for information sharing. The word "science" in most western European languages means knowledge in the broadest sense. Information Science encompasses the whole intellectual content of a library, and integrates all available forms of information within the relevant context. Its breadth is sometimes seen as a weakness but it is in fact its strength.


Prof. Dr. Michael Seadle has written on a wide range of subjects including research integrity, long term digital archiving, research methodology, copyright, digitization, computing management, and German history. He has been principal investigator on grants from the German Research Foundation (DFG), the National Science Foundation (NSF), and the Institute for Museum and Library Services (IMLS). His current research areas are research integrity and long term digital archiving.
Michael Seadle is previous Director of the Berlin School of Library and Information Science and previous Dean and previous Deputy Dean of the Humanities Faculty, previous chair of the Commission on Research Ethics and previous chair of the University Council at Humboldt-Universität zu Berlin. He was Editor and Editorial board member for several journals.
Currently he is a founding co-director of the HEADT Centre (Humboldt Elsevier Advanced Data and Text Centre) and Executive Director of the iSchools Organization.


On-Site Keynote

On-Site in Changchun, China: Wednesday, 24 April

9.00 am Local Time

Wei Lu

Wei Lu

Dean of School of Information Management

Wuhan University, China

Originality Evaluation Techniques based on the Processing and Understanding of Scientific Papers with AI

With the number of scientific papers is increasing rapidly, how to identify papers with great originality in a timely manner is a significant research problem. The AI technologies (e.g., LLM) present new approaches for processing, understanding, and evaluating scientific papers. In our report, first, we briefly introduce our research foundation, which focuses on utilizing AI technologies to process and understand scientific text. Subsequently, we report our two recent studies. In our first study, we analyze the feasibility of employing LLM to conduct originality evaluation in zero-shot learning. Specifically, we design a novel prompt and build two new evaluation datasets, and test originality evaluation performance on different LLMs. We find that LLM to some extent can serve as the qualified reviewer. However, LLM typically is overly tolerant reviewer, and therefore their evaluation performance is not perfect. To improve LLM’s evaluation performance, in our second study, we build a new rating dataset, and use QLoRA algorithm to fine-tune LLM, by which we can obviously improve their evaluation performance. Specifically, our model can effectively distinguish new papers published in journal with distinct Impact Factors only based on the research content. Finally, we introduce and demonstrate our newly developed Originality Evaluation System, which can generate Originality Score, Originality Type, and Originality Description to evaluate scientific papers.



Wei Lu is the Dean of the School of Information Management, Wuhan University. His research interests include knowledge organization, data intelligence, AI governance, etc. He has led more than ten research projects such as the National 2030 "New Generation Artificial Intelligence" major project, the major project funded by the National Social Science Foundation of China, and applied for more than 20 national standards, invention patents, and software copyrights. He has also developed software such as question answering robots (RobertAI), the scientific information intelligent processing platform (ScienceAI) and so forth. He has papers published on AAAI, ACL, SIGIR, EMNLP, JASIST, IP&M and Research Policy etc. He received the Excellent Achievement Award in Humanities and Social Sciences from the Ministry of Education, China and the Excellent Achievement Award in Social Sciences from Hubei Province. He also serves as a member of the Education Guidance Committee for Management Science and Engineering of the Ministry of Education, China, Vice Chairman of the China Index Society, Vice Chairman of the China Information Systems Professional Committee (CNAIS), and Executive Director of the China Science and Technology Information Society.

Sadao Kurohashi

Prof. Sadao Kurohashi


National Institute of Informatics

Tokyo, Japan

On-Site Keynote

On-Site in Changchun, China: Thursday, 25 April

9.00 am Local Time

From Data Platform
to Knowledge Infrastructure

In the 21st century, the significance of data has been distinctly recognized as a major trend in both academia and society. The digitalization of data and its open dissemination have led to substantial academic advancements. In Japan, with the National Institute of Informatics (NII) at the forefront, there has been a continuous development of network infrastructure leading up to SINET6 and the establishment of research data platforms.  Moving forward, for academic research to delve deeper as comprehensive knowledge and address complex societal challenges, it is imperative to automate data interpretation, relate and systematize knowledge, and construct a knowledge infrastructure that fosters the creation of new insights across disciplines. Given that the data infrastructure is in place and the value of open data has begun to be recognized, and with the advent of large language models (LLMs) rooted in machine translation research enabling sophisticated interpretation of papers and multimedia data, we can say that the groundwork for building a knowledge infrastructure has been set. This presentation introduces efforts to structure LLM research, development, and operational systems under broad academic collaboration, aiming for the construction of a knowledge infrastructure.



Sadao Kurohashi received a PhD in Electrical Engineering from Kyoto University in 1994.  He is currently the Director-General of the National Institute of Informatics, Japan, and a specially appointed professor at the Graduate School of Informatics at Kyoto University.

His research interests include natural language processing, knowledge infrastructure, and open science.  He received the 10th and 20th anniversary best paper awards from Journal of Natural Language Processing in 2004 and 2014, respectively, 2009 IBM faculty award, and the 2010 NTT DOCOMO mobile science award, and the 2017 Commendation for Science and Technology by the Minister of Education.

bottom of page