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Sherri Weitl-Harms

Associate Professor, Computer Science, Design, & Journalism · Creighton University

https://researchid.co/sherriweitlharms
@creighton.edu
19Scopus Publications
922Google Scholar Citations
14Google Scholar h-index
15Google Scholar i10-index

Research Interests

Education

Biography

Sherri Weitl-Harms is an Associate Professor of Computer Science at Creighton University. In addition to several years of industry experience, she has been in academia for more than twenty-five years and served as chair of the Cyber Systems department at the University of Nebraska at Kearney for 12 years. Her research areas include machine learning/artificial intelligence, natural language processing, CS education, gamification, and spatial-temporal data mining. She has numerous peer reviewed publications and has been involved with over $12 million in research grants. Dr. Weitl-Harms is heavily involved in undergraduate research, serves as a councilor of Math/CS for the Council for Undergraduate Research, and is actively committed to service learning, with student projects that have aided hundreds of local, regional, and national organizations. She is a program committee member and reviewer for several professional conferences/journals.

Education

• Ph.D., Computer Engineering & Computer Science, University of Missouri – Columbia, 2002 Cumulative GPA: 4.00/4.00. Dissertation: Associating and Predicting Episodes in Multiple Time Series for Supporting Policy Decision Making. • MS, Iowa State University, 1990. Major: Computer Science Thesis: Comparison of Nested Query Performance of Four Relational Database Management Systems. • BS, Buena Vista University, 1987. Major: Computer Science/Math/Education; Summa Cum Laude Iowa Teacher’s Certificate 234534, Endorsement in Secondary Education, Mathematics, 1987-1997.

Recent Scopus Publications

  1. Toward Automated Knowledge Discovery in Case-Based Reasoning
    Proceedings of the International Florida Artificial Intelligence Research Society Conference Flairs, 2024
  2. Iterative Service-Learning: A Computing-Based Case-study Applied to Small Rural Organizations
    Proceedings Frontiers in Education Conference Fie, 2024
  3. Using LLMs to Establish Implicit User Sentiment of Software Desirability
    Proceedings 2024 International Conference on Machine Learning and Applications Icmla 2024, 2024
  4. Utilizing Large Language Models to Synthesize Product Desirability Datasets
    Proceedings 2024 IEEE International Conference on Big Data Bigdata 2024, 2024
  5. Assessing User Experiences with ZORQ: A Gamification Framework for Computer Science Education
    Proceedings of the Annual Hawaii International Conference on System Sciences, 2023

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