Cheng Liu
Assistant Research Professor
Ph.D., University of Illinois at Urbana-Champaign
574-631-1168
1020 Jenkins Nanovic Hall
Profile
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