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Dr. Mary Elaine Califf

Associate Professor
School Information Technology
Office
Williams Hall - WIH 17A
  • About
  • Education
  • Research

Current Courses

279.001Algorithms And Data Structures

279.002Algorithms And Data Structures

327.001Concepts Of Programming Languages

327.003Concepts Of Programming Languages

Teaching Interests & Areas

Artificial Intelligence
Algorithms and Data Structures
Programming
Programming Languages
Compilers
Database
Writing

Research Interests & Areas

Natural Language Processing
Machine Learning
Computer Science Education

Ph D Computer Sciences

University of Texas at Austin
Austin, Texas

MS Computer Science

Baylor University
Waco, TX

MA English

Baylor University
Waco, TX

BA English

Baylor University
Waco, TX

Cited Research

Lavelli, A., Califf, M., Ciravegna, F., Freitag, D., Guiliano, C., Kushmerick, N., & Romano, L. A Critical Survey of the Methodology for IE Evaluation. Proceedings of the 4th International Conference on Language Resources and Evaluation (2004)

Conference Proceeding

Califf, M. Combining Rules and Naïve Bayes for Disease Classification. Second i2b2 Workshop on Challenges in Natural Language Processing for Clinical Data - AMIA (2008)
Califf, M., Goodwin, M., & Brownell, J. Helping him see: Guiding a visually impaired student through the computer science curriculum. Proceedings of the 39th SIGCSE Technical Symposium on Computer Science Education (2008)
Califf, M., & Goodwin, M. Effective incorporation of ethics into courses that focus on programming. Proceedings of the 36th SIGCSE Technical Symposium on Computer Science Education (2005)
Ireson, N., Ciravegna, F., Califf, M., Freitag, D., Kushmerick, N., & Lavelli, A. Evaluating machine learning for information extraction. Proceedings of the 22nd International Conference on Machine Learning (ICML 2005) (2005)
Lavelli, A., Califf, M., Ciravegna, F., Freitag, D., Guiliano, C., Kushmerick, N., & Romano, L. IE evaluation: Criticisms and recommendations. Proceedings of the AAAI-04 Workshop on Adaptive Text Extraction and Mining (ATEM-2004) (2004)

Journal Article

Lavelli, A., Califf, M., Ciravegna, F., Freitag, D., Guiliano, C., Kushmerick, N., Romano, L., & Ireson, N. Evaluation of Machine Learning-based Information Extraction Algorithms: Criticisms and recommendations. Language Resources and Evaluation 42.4 (2009)
Goodwin, M., & Califf, M. An assessment of the impact of time management training on success in a time-intensive course. Journal on Excellence in College Teaching 17.2 (2007)
Califf, M., & Mooney, R. Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction. Journal of Machine Learning Research 4 (2003): 177-210.
Califf, M., & Thompson, C. Improving Learning by Choosing Examples Intelligently in Two Natural Language Tasks. Learning Language in Logic (J. Cussens and S. Džeroski Eds.) (2000): 279-299.
Califf, M., & Mooney, R. Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming. New Generation Computing 16 (1998): 263-281.

Presentations

Mary Elaine Califf and Nick Dunne. 2022. Feedback in Context: Using a Code Review Tool for Program Grading. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2022). Association for Computing Machinery, New York, NY, USA, 92–97. https://doi.org/10.1145/3478431.3499402
Preliminary findings on the significance of learning styles over time. International Society for the Scholarship of Teaching and Learning Inaugural Meeting. (2004)

Grants & Contracts

Collaborative Research: ITWF: Building Communities: Recruiting and Retention of Underrepresented Groups in Computer Science. Illinois State University. (2004)