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Richard Appiah

Title: Clinical Assistant Professor

Department: ADA - Advanced Data Analytics

College: University of North Texas

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, Louisiana Tech University, 2017
    Major: Computational Analysis and Modeling
    Dissertation: Spatiotemporal Subspace Feature Tracking by Mining Dicriminatory Characteristics
  • MS, Louisiana Tech University, 2015
    Major: Mathematics
  • MS, University of Salford, 2005
    Major: Data Telecommunication and Networks
  • BS, University of Ghana, 2001
    Major: Computer Science and Statistics

Current Scheduled Teaching

ADTA 5340.004Discovery and Learning with Big DataSpring 2025 Syllabus
ADTA 5240.001Harvesting, Storing and Retrieving DataSpring 2025 Syllabus
ADTA 4340.700Methods for Discovery and Learning from DataSpring 8W2 2025
ADTA 4240.001Principles of Data Structures, Harvesting and WranglingSpring 2025 Syllabus
Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Previous Scheduled Teaching

ADTA 5340.003Discovery and Learning with Big DataFall 2024 Syllabus SPOT
ADTA 5240.004Harvesting, Storing and Retrieving DataFall 2024 Syllabus SPOT
ADTA 5240.402Harvesting, Storing and Retrieving DataFall 8W1 2024 Syllabus SPOT
ADTA 5240.402Harvesting, Storing and Retrieving DataSummer 8W1 2024 Syllabus SPOT
Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Published Intellectual Contributions

    Conference Proceeding

  • Appiah, R.D., Dua, S. (2017). Tracking feature relevance with the plaid model in continuously changing datasets. IEEE Proceedings. 1 (1) 20-24. London, UK, 2017 2nd International Conference on Knowledge Engineering and Applications (ICKEA). https://ieeexplore.ieee.org/document/8169895
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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
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