Mendoza School of Business

John Lalor

Assistant Professor
IT, Analytics, and Operations
  338B Mendoza College of Business
  • Biography
  • Background
  • Publications

John Lalor is an Assistant Professor of IT, Analytics, and Operations at the Mendoza College of Business. He completed his PhD at the University of Massachusetts Amherst in the College of Information and Computer Science. His research interests are in machine learning and natural language processing, specifically regarding model evaluation, quantifying uncertainty, model interpretability, and applications in biomedical informatics.

Prior to UMass, John worked as a software developer at Eze Software in Chicago and as an IT Audit Associate for KPMG. He has a Master's Degree in Computer Science from DePaul University, and a BBA degree in IT Management from Universty of Notre Dame, with a minor in Irish Language & Literature.

Ph D, University of Massachusetts-Amherst
MS, DePaul University
BBA, University of Notre Dame

"Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines", (With Ahmed Abbasi, Kezia Oketch, Yi Yang, Nicole Forsgren), ACM Transactions on Information Systems - Accepted (awaiting publication)

"The Effect of Bots on Human Interaction in Online Communities", (With Hani Safadi, Nicholas Berente), MIS Quarterly - Accepted (awaiting publication)

"Evaluating the Efficacy of NoteAid on EHR Note Comprehension among US Veterans through Amazon Mechanical Turk", (With Hao Wu, Kathleen Mazor, Hong Yu), International Journal of Medical Informatics

"Business Analytics in Healthcare: Past, Present, and Future Trends", (With Kaitlin Wowak, Sriram Somanchi, Corey Angst), Manufacturing and Service Operations Management

"Py-IRT: A Scalable Item Response Theory Library for Python", (With Pedro Rodriguez), INFORMS Journal on Computing, 2022

"Evaluating the Effectiveness of NoteAid in a Community Hospital Setting: Randomized Control Trial", (With Wen Hu, Matthew Tran, Hao Wu, Kathleen Mazor, Hong Yu), Journal of Medical Internet Research, 2021