5 papers
Analyzing Curricular Pattern Complexity Using AI to Improve On-Time Graduation Rates
Lynn Vonderhaar, Juan Couder, Siri Siqveland +2
The rise of Artificial Intelligence (AI) enables automatic analysis of large amounts of data. Previously time-consuming and labor-intensive tasks can be completed much more efficie…
WIP: Software Engineering Competencies in the Age of AI
Lynn Vonderhaar, Massood Towhidnejad, Omar Ochoa
A university education is meant to fully prepare graduates to enter and succeed in the workforce in their field. Accreditation bodies and professional organizations help to achieve…
Verifying Machine Learning Interpretability Requirements through Provenance
Lynn Vonderhaar, Juan Couder, Daryela Cisneros +1
Machine Learning (ML) Engineering is a growing field that necessitates an increase in the rigor of ML development. It draws many ideas from software engineering and more specifical…
Embedding Provenance in Computer Vision Datasets with JSON-LD
Lynn Vonderhaar, Timothy Elvira, Tyler Thomas Procko +1
With the ubiquity of computer vision in industry, the importance of image provenance is becoming more apparent. Provenance provides information about the origin and derivation of s…
Towards Robust Training Datasets for Machine Learning with Ontologies: A Case Study for Emergency Road Vehicle Detection
Lynn Vonderhaar, Timothy Elvira, Tyler Procko +1
Countless domains rely on Machine Learning (ML) models, including safety-critical domains, such as autonomous driving, which this paper focuses on. While the black box nature of ML…