Skip to main content

Haihua Chen

Title: Assistant Professor

Department: Data Science

College: College of Information

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, University of North Texas, 2022
    Major: Information Science
    Dissertation: Data Quality Evaluation and Improvement for Machine Learning

Current Scheduled Teaching

HINF 5506.020Applications of Artificial Intelligence in HealthSpring 2025 Syllabus
INFO 5731.020Computational Methods for Information SystemsSpring 2025 Syllabus
INFO 6900.728Special ProblemsSpring 2025

Previous Scheduled Teaching

INFO 5731.020Computational Methods for Information SystemsFall 2024 SPOT
INFO 6900.044Special ProblemsFall 2024
INFO 5810.002Data Analysis and Knowledge DiscoverySummer 10W 2024 SPOT
INFO 5506.020Artificial Intelligence in HealthSpring 2024 SPOT
INFO 5731.020Computational Methods for Information SystemsSpring 2024 SPOT
INFO 5731.021Computational Methods for Information SystemsSpring 2024 SPOT
INFO 5731.022Computational Methods for Information SystemsSpring 2024 SPOT
INFO 6900.733Special ProblemsSpring 2024
INFO 5731.020Computational Methods for Information SystemsFall 2023 SPOT
INFO 5810.002Data Analysis and Knowledge DiscoverySummer 10W 2023 SPOT
INFO 6900.719Special ProblemsSummer 5W2 2023
INFO 5731.020Computational Methods for Information SystemsSpring 2023 SPOT
INFO 5810.001Data Analysis and Knowledge DiscoverySpring 2023 SPOT
INFO 5810.002Data Analysis and Knowledge DiscoverySpring 2023 SPOT
INFO 5731.020Computational Methods for Information SystemsFall 2022 SPOT
INFO 5810.001Data Analysis and Knowledge DiscoveryFall 2022 SPOT
INFO 5810.002Data Analysis and Knowledge DiscoveryFall 2022 SPOT
INFO 5810.002Data Analysis and Knowledge DiscoverySummer 10W 2022 SPOT
INFO 5502.002Principles and Techniques for Data ScienceSummer 5W2 2022 SPOT
INFO 5731.002Computational Methods for Information SystemsSpring 2022 SPOT
INFO 5502.004Principles and Techniques for Data ScienceSpring 2022 SPOT
INFO 5731.002Computational Methods for Information SystemsFall 2021 SPOT
INFO 5731.002Computational Methods for Information SystemsSpring 2021 Syllabus SPOT
INFO 5731.203Computational Methods for Information SystemsSpring 2021 Syllabus SPOT
INFO 5731.202Computational Methods for Information SystemsFall 2020 Syllabus SPOT
INFO 5731.002Computational Methods for Information SystemsSpring 2020 Syllabus
INFO 4206.001Information Retrieval SystemsSpring 2019 Syllabus SPOT

Published Intellectual Contributions

    Conference Proceeding

  • Zhang, X., Chen, H., Chong, M., Hagen, L. (2024). A Framework for Assessing Country Reputation: Case Study of China during the COVID-19 Pandemic. New York, Association for Computing Machinery. https://dl.acm.org/doi/proceedings/10.1145/3657054
  • Nguyen, H., Chen, H., Maganti, R., Hossain, T., Ding, J. Identifying High-quality Informative Comments for Software Review Summarization. IEEE AITest.
  • Qin, C., , Y.Y., Chen, H., Ding, J. (2021). A Comparison Study of Machine Learning and Deep Learning for Legal Contract Understanding. JURISIN 2021: 15 Intl. Workshop on Juris-informatics.
  • Chen, J., Chen, H., Tang, M. (2020). An Ontology-based Semantic Information Retrieval System. IEEE.
  • Chen, J., Chen, H., Tang, M. (2020). Smart bookshelf for library book management. Proceedings of the Association for Information Science and Technology, 2020..
  • Chen, H., Cao, G., Chen, J., Ding, J. (2019). A Practical Framework for Evaluating the Quality of Knowledge Graph. Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding. 12. Singapore, Springer.
  • Journal Article

  • Wang, Z., Peng, S., Chen, J., Zhang, X., Chen, H. (2023). ICAD-MI: Interdisciplinary concept association discovery from the perspective of metaphor interpretation. Knowledge-Based Systems. 275 110695. Elsevier BV. http://dx.doi.org/10.1016/j.knosys.2023.110695
  • Tran, N., Chen, H., Bhuyen, J., Ding, J. (2022). Data Curation and Quality Evaluation for Machine Learning-Based Cyber Intrusion Detection. IEEE Access. 10 121900 - 121923. IEEE.
  • Chen, H., Pieptea, L., Ding, J. (2022). Construction and Evaluation of a High-Quality Corpus for Legal Intelligence Using Semiautomated Approaches. IEEE Transactions on Reliability. 71 (2) 1-17. IEEE.
  • Chen, H., Wu, L., Chen, J., Lu, W., Ding, J. (2021). A comparative study of automated legal text classification using random forests and deep learning. Information Processing & Management. 59 (2) Elsevier.
  • Tran, N., Chen, H., Jiang, J., Bhuyan, J., Ding, J. (2021). Effect of Class Imbalance on the Performance of Machine Learning-based Network Intrusion Detection. International Journal of Performability Engineering. 17 (9) Totem.
  • Cartwright, A.D., Carey, C.D., Chen, H. (2021). Multi-tiered intensive supervision: A culturally-informed method of clinical supervision. Teaching and Supervision in Counseling. https://trace.tennessee.edu/tsc/
  • Chen, H., Chen, J., Ding, J. (2021). Data Evaluation and Enhancement for Quality Improvement of Machine Learning. IEEE Transactions on Reliability. 70 (2) IEEE.
  • Chen, J., Chen, H., Tang, M. (2020). An ontology-improved vector space model for semantic retrieval. The Electronic Library.
  • Chen, J., Lu, W., Chen, H. (2019). Result Diversification in Image Retrieval Based on Semantic Distance. Denton,
  • Cui, J., Ma, Y., Zhang, J., Chen, H., Fang, R. (1996). Growth and characterization of diamond film on aluminum nitride. Materials Research Bulletin. 31 (7) 781--785. Pergamon.

Contracts, Grants and Sponsored Research

    Grant - Research

  • Ding, J. (Principal), Kinshuk, X. (Co-Principal), Fu, S. (Co-Principal), Ludi, S.A. (Co-Principal), Chen, H. (Co-Principal), Hossain, T. (Co-Principal), Xiao, T. (Co-Principal), Feng, Y. (Co-Principal), Cleveland, A.D. (Co-Principal), Smith, D.L. (Co-Principal), Mankins, N. (Co-Principal), Booker, D.D. (Co-Principal), Carrillo, D. (Co-Principal), "NSF Includes ARISE Alliance Membership," sponsored by Arizona State University, Other, $64800 Funded. (2024 - 2027).
  • Xiao, T. (Principal), Ding, J. (Co-Principal), Albert, M.V. (Supporting), Alam, Z.S. (Supporting), Hartmann, F. (Supporting), Wang, Y. (Supporting), Liang, L. (Supporting), Chen, H. (Supporting), Du, J. (Supporting), Azad, R.K. (Supporting), "NSF REU site: Beyond Language: Training to Create and Share Vector Embeddings across Application," sponsored by NSF, Federal, $403547 Funded. (2023 - 2025).
  • Sponsored Research

  • Ding, J., Ludi, S.A., Fu, S., Kinshuk, K., Chen, H., "Developing a High-Quality Academic Environment for Broadening Participation of Hispanic Students in Computing," sponsored by NSF, Federal, $499517 Funded. (2022 - 2025).
,
Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
CLOSE