1. Courses offered lately:
CSCI 2330 Discrete math
CSCI 3330 Algorithms
CSCI 4310/5310 Numerical methods for data science
CSCI 4v95/5v95 Research project/independent study
CSCI 6330 Topics on algorithms
CSCI 6397 Special topics
CSCI 6v99 Master's thesis
2. Selected grant awards:
NSF/OIA-1946391, Senior scientist, Data Analytics that are Robust and Trusted (DART): From Smart Curation to Socially Aware Decision Making
NSF/CISE/CCF-0727798, PI (Principal Investigator), Knowledge Processing with Interval Methods
NSF/CISE/CCF-0202042, PI, Parallel Reliable Global Optimization with Interval Arithmetic
Army Research Office, DAAH-0495-1-0250, Co-PI, Parallel and Distributed Evaluation, Visualization, and AI Reasoning to Advanced Distributed Interactive Simulation Technology
3. Selected publications: (Student co-authors are specified with an underline)
Hu, C., (2025). How do we sort an interval-valued dataset? IFSA-NAFIPS 2025, Banff, Canada, August 15-19, 2025.
Hu, C., (2024). An extended one-way ANOVA algorithm for analyzing interval-valued experiments. IEEE WCCI 2024, Yokohama, Japan, June 30-July 5, 2024. http://dx.doi.org/10.1109/FUZZ-IEEE60900.2024.10611862.
Hu, C., Spurling, M. (2023). Dynamically Monitoring Crowdworker's Reliability with Interval-Valued Labels. Best Paper Award in Artificial Intelligence and Social Computing at the AHFE (2023) International Conference, San Francisco, CA July 20-24, 2023. AHFE Open Access, vol 72. http://doi.org/10.54941/ahfe1003270
Moody, A., Spurling, M., Hu, C. (2023). The Removal of Irrelevant Human Factors in a Multi-Review Corpus through Text Filtering. In: Tareq Ahram (eds) Human Factors in Software and Systems Engineering. AHFE (2023) International Conference. AHFE Open Access, vol 94. AHFE International, USA. http://doi.org/10.54941/ahfe1003766
Spurling, M., Hu, C., Zhan, H., Sheng, V.S. (2022). Anomaly Detection in Crowdsourced Work with Interval-Valued Labels. In: Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2022. Communications in Computer and Information Science, vol 1601. Springer, Cham. https://doi.org/10.1007/978-3-031-08971-8_42
Moody, A., Hu, C., Zhan, H., Spurling, M., Sheng, V.S. (2022). Towards Explainable Summary of Crowdsourced Reviews Through Text Mining. In: Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2022. Communications in Computer and Information Science, vol 1601. Springer, Cham. https://doi.org/10.1007/978-3-031-08971-8_44
M. Spurling, C. Hu, X. Zhan, and VS. Sheng (2021) Estimating crowd-worker's reliability with interval-valued labels to improve the quality of crowdsourced work, Proc. IEEE SSCI 2021, Orlando FL, Dec. 5-7, 2021, DOI: 10.1109/SSCI50451.2021.9660043.
C. Hu, V.S. Sheng, N. Wu, and X. Wu (2021) Managing uncertainty in crowdsourcing with interval-valued labels. NAFIPS 2021: 166-178, DOI: 10.1007/978-3-030-82099-2_15
C.Hu and Z. Hu (2020) On Statistics, Probability, and Entropy of Interval-Valued Datasets. IPMU (3) 2020: 407-421, https://doi.org/10.1007/978-3-030-50153-2_31
C. Hu and Z. Hu (2020) A Computational Study on the Entropy of Interval-Valued Datasets from the Stock Market. IPMU (3) 2020: 422-435, https://doi.org/10.1007/978-3-030-50153-2_32
C. Rhodes, J. Lemon, C. Hu (2015) An Interval-Radial Algorithm for Hierarchical Clustering Analysis, Int. Conf. on Machine Learning and Application, pp. 849-856, Miami, FL. https://doi.org/10.1109/ICMLA.2015.118
C. Mitchel, C. Hu, B. Chen, M. Nooner, P. Young (2014) A Computational Study on Interval-Valued Matrix Games, the 2014 Int. Conf. on Computational Science and Computational Intelligence, Las Vegas, NV. https://doi.org/10.1109/CSCI.2014.66
B. Nordin, C. Hu, B. Chen, and V. Sheng (2012) Interval-Valued Centroids in K-Means Algorithms, Int. Conf., Machine Learning and Applications, Vol. 1, pp. 478-481, Boca Raton, FL. https://doi.org/10.1109/ICMLA.2012.87
P. Marupally, V. Paruchuri, C. Hu (2012) Bandwidth Variability Prediction with Rolling Interval Least Squares, ACM 50th Southeast Reginal Conference, pp. 209-213, Tuscaloosa, AL. https://doi.org/10.1145/2184512.2184562
V. Yip, S. Kockara, and C. Hu (2011) Efficient Calculation of Structural Similarity Threshold for the SCAN Network Clustering Algorithm, IEEE Int. Conf. on Bioinformatics and Biomedicine, pp. 600-603, Atlanta, GA. https://doi.org/10.1109/BIBM.2011.49
C. Hu (2011) Interval function and its linear least-squares approximation, the ACM 4th International Workshop on Symbolic and Numeric Computation, pp. 16-23, San Jose, CA. https://doi.org/10.1145/2331684.2331689
L. He and C. Hu (2010) Midpoint method and accuracy of variability forecasting, J. Empirical Economics, 38, 705-715. https://doi.org/10.1007/s00181-009-0286-6
L. He and C. Hu (2009) Impacts of interval computing on stock market variability forecasting, J. of Computational Economics, 33(3), 263-276. https://doi.org/10.1007/s10614-008-9159-x
C. Hu, B. Kearfott, A. de Korvin and V. Kreinovich (2008) Book: Knowledge Processing with Interval and Soft Computing, Springer, ISBN 978-1-84800-325-5.
D. Collins and C. Hu (2008) Studying interval valued matrix games with fuzzy logic, J. of Soft Computing, 12(2), 147-155. DOI:10.1007/s00500-007-0207-6
C. Hu and L. He (2007) An application of interval methods to stock market forecasting J. Reliable Computing 13(5): 423-434. DOI:10.1007/s11155-007-9039-4
IEEE SA 1788: IEEE Standard for Interval Arithmetic, Member for IEEE Interval Standard Working Group - P1788.
ABET Computing Accreditation Commission, commissioner (2016-2019) and program evaluator (2004-2019).
Chairperson of the Department of Computer Science at the University of Central Arkansas (2002-2013).
Served as a panelist and/or committee member on NSF/CISE grant reviews.
Served as co-chair and/or member of program/organizing committee for international professional conferences.
Reviewer for professional journals and conferences.