Yang Yang is an Assistant Professor of IT, Analytics, and Operations. Yang holds a PhD in Computer Science from the University of Notre Dame. He was an Assistant Professor at Syracuse University. Before that, he was a Research Assistant Professor at Kellogg School of Management. His principal research interest lies in the areas of data mining/machine learning, computational social science and science of science. Yang is interested in studying how social networks affect individuals' success. Specifically, he has studied the link between social network and leadership attainment. He also focuses on research in the context of science and innovation. He studies the effect of team composition on performance and innovation, as well as the role of media and social media in shaping public access to science. His work has been published in journals and conference proceedings, such as Proceedings of the National Academy of Sciences, KDD, ICDM, WWW and Knowledge and Information Systems. His papers have been mentioned by Forbes, Fortune, The Washington Post, BBC, Psychology Today, The Hill, WIRED, and Harvard Business Review.
"Gender-diverse teams produce more novel and higher-impact scientific ideas", IC2S2: 8th International Conference on Computational Social Science, 2022
"Estimating the deep replicability of scientific findings using human and artificial intelligence", OECD Workshop - AI and the Productivity of Science, 2021
"Gender Diverse Teams Produce More Innovative and Influential Ideas in Medical Research", MIT Sloan - WOS Seminars, 2021
"Gender Diverse Teams Produce More Innovative and Influential Ideas in Medical Research", NBER Workshop on the Science of Science Funding, 2021
"A network's gender composition and communication pattern predict women's leadership success", INFORMS Annual Meeting, Seattle, 2019
"Media and Public Perception to Science", INFORMS Annual Meeting, Seattle, 2019
"The Replicability of Scientific Findings Using Human and Machine Intelligence", INFORMS Annual Meeting, Seattle, 2019
"The Replicability of Scientific Findings Using Human and Machine Intelligence", Metascience Symposium, Stanford University, 2019
"The Replicability of Scientific Findings Using Human and Machine Intelligence", Academy of Management Annual Meeting, Boston, 2019
"A networks' gender composition and communication pattern predict women's leadership success", NetSci Annual Meeting, Vermont, 2019
"Quantifying the Future Lethality of Terror Organizations", NetSci Annual Meeting, Vermont, 2019
"Social Networks Predict Placement in Leadership Positions: A Gender Perspective", Academy of Management Annual Meeting, Chicago, 2018
"AI + Mind Partnership and the Reproducibility Problem in Science", Computational Sociology Workshop, Philadelphia, 2018
"The Inner Circles of Women's Networks Predict their Job Attainment in Leadership Positions", NetSci Annual Meeting, Indianapolis, 2017
