Cheng Liu

Cheng Liu

Assistant Research Professor

Ph.D., University of Illinois at Urbana-Champaign


1020 Jenkins Nanovic Hall

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Dr. Cheng Liu’s primary research interests are computational modeling, data mining, and their applications in psychology, biology, computer engineering, and education. Dr. Cheng Liu also serves as a Computational Scientist in the Center for Research Computing (CRC) and Data Scientist for the Center for Social Science Research (CSSR) at University of Notre Dame. He has years of hands-on experience in big data analytics and statistical modeling, as well as scientific computing and software development. He is currently serving as co-PI on two federally funded projects, in charge of the development of educational assessment platform and survey data analytics platform.

Recent Publications

Liu, C., Han, K. T., & Li, J. (2019). Compromised item detection for computerized adaptive testing. Frontiers in Psychology. doi: 10.3389/fpsyg.2019.00829

Liu, C., & Cheng Y. (2018). An application of the support vector machine for attribute-by-attribute classification in cognitive diagnosis. Applied Psychological Measurement, 42(1), 58-72. doi: 10.1177/0146621617712246

Cheng, Y., & Liu, C. (2016). A note on the relationship between pass rate and multiple attempts. Journal of Educational Measurement, 53(4), 431-447. doi:10.1111/jedm.12124

McBurney, P. W., Liu, C., & McMillan, C. (2016). Automated feature discovery via sentence selection and source code summarization. Journal of Software: Evolution and Process, 28(2), 120-145. doi: 10.1002/smr.1768

Schiedler, N. H,. Liu, C., Hamby, K. A., Zalom, F. G., & Syed, Z. (2015). Volatile codes: evolution of olfactory signals and reception in drosophila-yeast chemical communication. Nature Scientific Reports, 5, 14059. doi: 10.1038/srep14059

Rodeghero, P., Liu, C., McBurney, P. W., & McMillan, C. (2015). An eye-tracking study of Java programmers and application to source code summarization. IEEE Transactions on Software Engineering, 41(11), 1038-1054. doi: 10.1109/TSE.2015.2442238

Cheng, Y., Liu, C., & Behrens, J. (2015). Standard error of ability estimates and the classification accuracy and consistency of binary decisions in linear and adaptive testing. Psychometrika, 80(3), 645-664. doi: 10.1007/s11336-014-9407-z

Cheng, Y., & Liu, C. (2015). The effect of upper and lower asymptotes of IRT models in computerized adaptive testing. Applied Psychological Measurement. 39(7), 551–565. doi: 10.1177/0146621615585850