Dr. Jaelle Scheuerman's Research Home

About

I am a computer scientist working in the area of Human-AI collaboration. My research explores interactive machine learning, cognitive modeling, activity recognition and preference learning. I love working with interdisciplinary teams and am particularly interested in AI that helps people work, play, and live in meaningful ways. I received my PhD (2015-2020) from the Department of Computer Science at Tulane University, where I was supervised by K. Brent Venable.

Select Publications

A Framework for Enhancing Behavioral Science Research with Human-Guided Language Models
Jaelle Scheuerman, Dina M. Acklin, AAAI Symposium on Machine Learning and Knowledge Engineering, 2024
Visual Preferences in Map Label Placement
Jaelle Scheuerman, Jason L. Harman, Rebecca R. Goldstein, Dina M. Acklin, Chris J. Michael, Discover Psychology, 2023
Closed-Loop Uncertainty: The Evaluation and Calibration of Uncertainty for Human–Machine Teams under Data Drift
Zach Bishof, Jaelle Scheuerman, Chris J. Michael, Entropy, 2023
Simple Rules Outperform Machine Learning for Personnel Selection: Insights from the 3rd Annual SIOP Machine Learning Competition
Jason L. Harman, Jaelle Scheuerman, Discover Artificial Intelligence, 2023
Designing Interactive Machine Learning Systems for GIS Applications
Jaelle Scheuerman, Chris J. Michael, Brad Landreneau, Dina M. Acklin & Jason L. Harman, AAAI 2021 Spring Symposium on "Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities"
Auditory Spatial Attention Gradients and Cognitive Control as a Function of Vigilance
E.J. Golob, J.T. Nelson, J. Scheuerman, K.B. Venable, J.R. Mock, Psychophysiology, 2021
Modeling Voters in Multi-Winner Approval Voting
Jaelle Scheuerman, Jason L. Harman, Nicholas Mattei, K. Brent Venable, Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021.
On Interactive Machine Learning and the Potential of Cognitive Feedback
Chris J. Michael, Dina Acklin, Jaelle Scheuerman, 2nd Workshop on Deep Models and Artificial Intelligence for Defense Applications, 2020.
Dissertation: Computational Models of Heuristics and Bias in Human Behavior
Front Matter · Chapter 1: Introduction · Chapter 2: Preliminaries · Chapter 3: Bias in a Spatial Auditory Attention Task · Chapter 4: Confirmation Bias in a Probabilistic Learning Task · Chapter 5: Heuristics and Biases in Approval Voting · Chapter 6: Conclusion · Bibliography