Meijun Liu

Dr. Meijun Liu is an assistant professor at Institute for Global Public Policy, Fudan University. She got her BA in Archive Science from Sichuan University and Ph.D. in Information Science from the University of Hong Kong. Her research foci include big data analysis and application, science of science, science and technology policy and music information retrieval. Now she is interested in using large-scale datasets and data science techniques to explore how scientific collaboration and mobility influence research outputs and teams’ success, and collective music emotion during pandemics. Her recent articles appear in 《Journal of Informetrics》, 《Journal of Information Science》, 《PloS one》，《Learned Publishing》and《Quality & Quantity》. Her research articles received more than 70 citations. She serves as referees for high-quality international conferences and SSCI journals.

Research interestsbig data analysis and application, science of science, science and technology policy and music information retrieval

Academic positions

• 2020.11 – present, Assistant Professor, Institute for Global Public Policy, Fudan University

• 2020.09-2020.11, Lecture, Education Faculty, the University of Hong Kong

• 2020.01-2020.06, Visiting Scholar, California University (Merced)

• 2019.01-2019.08, Visiting Scholar, Department of Management and Organization, Northwestern University

• 2019.01-2019.08, Visiting Scholar, Northwestern Institute on Complex Systems (NICO), Northwestern University

• 2017.09-2018.08, Faculty Associate, Department of Economics, Harvard University

• 2017.09-2018.08, Visiting Scholar, National Bureau of Economic Research (NBER)

Education

• 2016-2020，Ph.D in Information Science，the University of Hong Kong

• 2015-2016，Master student in Information Science，Zhejiang University

• 2011-2015, B.A. in Archive Science, Sichuan University

Academic Papers

In English

• Bu, Y., Li, H., Wei, C., Liu, M., & Li, J. (2020). On the relationship between supervisor–supervisee gender difference and scientific impact of doctoral dissertations: Evidence from Humanities and Social Sciences in China. Journal of Information Science, 0165551520969935.

• Liu, M., Hu, X., & Schedl, M. (2018). The relation of culture, socio-economics, and friendship to music preferences: A large-scale, cross-country study. PloS one, 13(12), e0208186.

• Liu, M., Hu, X., Wang, Y., & Shi, D. (2018). Survive or perish: Investigating the life cycle of academic journals from 1950 to 2013 using survival analysis methods. Journal of Informetrics, 12(1), 344-364.

• Liu, M., Hu, X., & Li, J. (2018). Knowledge flow in China’s humanities and social sciences. Quality & Quantity, 52(2), 607-626.

• Liu, M., Shi, D., & Li, J. (2017). Double-edged sword of interdisciplinary knowledge flow from hard sciences to humanities and social sciences: Evidence from China. PloS one, 12(9), e0184977.

• Wang, Y., Hu, R., & Liu, M. (2017). (corresponding)The geotemporal demographics of academic journals from 1950 to 2013 according to Ulrich’s database. Journal of Informetrics, 11(3), 655-671.

• Wang, Y., Chen, Y., Liu, M., & Hu, R. (2018). Growth and quality of Chinese journals from 1949 to 2013. Learned Publishing, 31(3), 205-214.

Conference Papers

• Liu, M., Zangerle, E., Hu, X., Melchiorre, A., & Schedl, M.. (2020). Pandemics, Music, and Collective Sentiment: Evidence from the Outbreak of COVID-19. International Society for Music Information Retrieval Conference.

• Hu, X. , Tam, I. , Liu, M. , & Downie, J. . (2018). Music artist similarity: an exploratory study on a large-scale dataset of online streaming services.

• Liu, M. , Hu, X. , & Schedl, M. . (2017). Artist Preferences and Cultural, Socio-economic Distances Across Countries: A Big Data Perspective. International Society for Music Information Retrieval Conference.

• Shi, D., & Liu, M. (2017). Age and team of great scientific discoveries in China. In Atlanta Conference on Science and Innovation Policy 2017 Abstract Book. Atlanta, GA.

In Chinese

• Liu, M., Li W., Wang, Y., & Chen, J.. (2015). The analysis of technology creation and diffusion networks based on the data on universities from 2008 to 2012. Forum on Science and Technology in China (中国科技论坛), (12), 101-107.（《技术创造-扩散网络对比研究——基于省际 2008—2012 年高校数据.》）

• Wang, Y., Liu M., Ma Q., & Chen, J.. (2015). Analysis on Strategic Emerging Industries' Patent Licensing of Chinese Universities. R & D Management (研究与发展管理), 27(4), 130-138.（《我国高校战略性新兴产业专利许可研究》）

Research projects

• Labor and Artificial Intelligence at Harvard University and NBER sponsored by IBM, 2018

• Cellular Agriculture at Harvard University, 2018

• Research on knowledge path under the background of cross discipline, The National Natural Science Fund, National Natural Science Foundation of China, 2016-2020

• Music Recommender Systems Based on Physiological Signals, Young Scholar Science Fund, National Natural Science Foundation of China, 2018 – 2020

Research grants

• ICGS grant from the International Finance Corporate (IFC) within the World Bank, 2018

• Travel grant from international society for music information (ISMIR) retrieval, 2017

• Faculty Research Travel Grant for Full-time MPhil and PhD Students, 2017

• The recognition award in the forum of Science & Technology Progress and Policy, 2016