Journal Articles

• J.P. Lalor, H. Wu, K. Mazor. H. Yu. Evaluating the Efficacy of NoteAid on EHR Note Comprehension among US Veterans through Amazon Mechanical Turk. International Journal of Medical Informatics. Forthcoming.
• K.D. Wowak, J.P. Lalor, S. Somanchi, C. Angst. Business Analytics in Healthcare: Past, Present, and Future Trends. Manufacturing and Service Operations Management. Forthcoming.
• J.P. Lalor, P. Rodriguez. py-irt: A Scalable Item Response Theory Library for Python. INFORMS Journal on Computing. 2022. doi:10.1287/ijoc.2022.1250
• J.P. Lalor, W. Hu, M. Tran, H. Wu, K. Mazor, H. Yu. Evaluating the Effectiveness of NoteAid in a Community Hospital Setting: Randomized Control Trial. J Med Internet Res 2021;23(5):e26354
• J. Chen, J.P. Lalor, W. Liu, E. Druhl, E. Granillo, V. Vimalananda, H. Yu. Detecting Hypoglycemia Incidents Reported in Patients Secure Messages: Using Cost-sensitive Learning and Oversampling to Reduce Data Imbalance. J Med Internet Res 2019;21(3):e11990. doi:10.2196/11990.
• J.P. Lalor, B. Woolf, H. Yu. Improving EHR Note Comprehension with NoteAid: A Randomized Trial of EHR Note Comprehension Interventions with Crowdsourced Workers, J Med Internet Res 2019;21(1):e10793.
• J.P. Lalor, H. Wu, L. Chen, K. Mazor, H. Yu. ComprehENotes, an Instrument for Assessing Patient Electronic Health Record Note Reading Comprehension: Development and Validation, J Med Internet Res 2018;20(4):e139.

Conference Publications

• J. P. Lalor, Y. Yang, K. Smith, N. Forsgren, A. Abbasi. Benchmarking Intersectional Biases in NLP. NAACL 2022.
• A. Abbasi, D. Dobolyi, J. P. Lalor, R. Netemeyer, K. Smith, and Y. Yang. Constructing a Psychometric Testbed for Fair Natural Language Processing. EMNLP 2021.
  • Authors listed alphabetically
• H. Safadi, J.P. Lalor, N. Berente. The Effect of Bots on Human Interaction in Online Communities. ICIS 2021.
  • Best Theory Paper
• N. Berente, J.P. Lalor, S. Somanchi, A. Abbasi. The Illusion of Certainty and Data-Driven Decision Making in Emergent Situations. ICIS 2021.
• P. Rodriguez, J. Barrow, A.M. Hoyle, J.P. Lalor, R. Jia and J. Boyd-Graber. Rethinking NLP Leaderboards with Methods from Educational Testing. ACL 2021. [project page]
• J.P. Lalor, H. Yu. Dynamic Data Selection for Curriculum Learning via Ability Estimation. Findings of ACL: EMNLP 2020.
• J.P. Lalor, H. Wu, H. Yu. Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds. EMNLP 2019. [code]
• J.P. Lalor, H. Wu, T. Munkhdalai, H. Yu. Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study. In EMNLP 2018. [youtube link for presentation]
• J.P. Lalor, H. Wu, H. Yu. Building an Evaluation Scale using Item Response Theory, In EMNLP 2016.
• C. Miller, A. Settle, and J.P. Lalor. Learning Object-Oriented Programming in Python: Towards an Inventory of Difficulties and Testing Pitfalls, SIGITE 2015.
• A. Settle, J.P. Lalor, and T. Steinbach. Evaluating a Linked-courses Learning Community for Development Majors. In SIGITE 2015.
• A. Settle, J.P. Lalor, and T. Steinbach. A Computer Science Linked-courses Learning Community, In ITiCSE 2015.
• A. Settle, J.P. Lalor, and T. Steinbach. Reconsidering the Impact of CS1 on Novice Attitudes. In SIGCSE 2015.

Workshop Presentations, Posters, and Abstracts

• M. Ma, J.P. Lalor. An Empirical Analysis of Human-Bot Interaction on Reddit. Workshop on Noisy User-generated Text (W-NUT), 2020.
• J.P. Lalor, H. Guo. Towards Measuring Algorithmic Interpretability. INFORMS Workshop on Data Science, 2020.
• E. Cho, H. Xie, J.P. Lalor, V. Kumar, W.M. Campbell. Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity. ASRU 2019
• J.P. Lalor, H. Wu, H. Yu. Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds. NAACL Workshop on Shortcomings in Vision and Language (SiVL) 2019 [poster]
• J.P. Lalor, H. Wu, H. Yu. Comparing Human and DNN-Ensemble Response Patterns for Item Response Theory Model Fitting. NAACL Workshop on Cognitive Modeling and Computational Linguistics (CMCL) 2019 [poster]
• J.P. Lalor, H. Wu, H. Yu. Soft Label Memorization-Generalization for Natural Language Inference. UAI Workshop on Uncertainty in Deep Learning., 2018.
• J. Chen, J.P. Lalor, H. Yu. Detecting Hypoglycemia Incidents from Patients' Secure Messages. American Medical Informatics Association (AMIA) Annual Symposium Poster, 2018
• J.P. Lalor, H. Wu, H. Yu, Modeling Difficulty to Understand Deep Learning Performance. Northern Lights Deep Learning Workshop (NLDL), 2018 [slides]
• J.P. Lalor, H. Wu, L. Chen, K. Mazor, H. Yu, Generating a Test of Electronic Health Narrative Comprehension with Item Response Theory. American Medical Informatics Association (AMIA) Annual Symposium Podium Abstract, 2017. [slides]
• J.P. Lalor, H. Wu, H. Yu. CIFT: Crowd-Informed Fine-Tuning to Improve Machine Learning Ability, HCOMP 2017 Works in Progress [poster]
• T. Munkhdalai, J.P. Lalor, H. Yu. Citation Analysis with Neural Attention Models, In LOUHI 2016 EMNLP Workshop.