Sarah A. Kusumastuti, PhD

Sarah A. Kusumastuti, PhD

she/her

Assistant Professor in Human-AI interaction and data science

Posts by Collection

portfolio

publications

Practice improves performance of a 2D uncertainty integration task within and across visualizations.

Published in IEEE Transactions on Visualization and Computer Graphics, 2022

Abbreviated Abstract: Information uncertainty is ubiquitous in everyday life. In this study, we examine whether brief, focused practice can improve people’s ability to understand and integrate bivariate Gaussian uncertainty visualized via ensemble displays, summary displays, and distributional displays, and we examine whether this is influenced by the complexity of the displayed information. In two experiments (N=118 and 56), decision making was faster and more accurate after practice relative to before practice. Furthermore, the performance improvements transferred to use of display types that were not practiced.

Recommended citation: Kusumastuti, S.A., Pollard, K.A., Oiknine, A.H., Dalangin, B., Raber, T.R., & Files, B.T. (2022). Practice improves performance of a 2D uncertainty integration task within and across visualizations. IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/TVCG.2022.3173889
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A simulation approach to investigate factors influencing the cost of omitted objectives in multiattribute models

Published in Journal of Multi‐Criteria Decision Analysis, 2023

Abbreviated Abstract: Empirical evidence suggests that decision-makers are ill-equipped to identify all relevant objectives in a decision problem. We examine the effect of an incomplete set of objectives using a Monte Carlo simulation to compare a baseline model to a reduced model incorporating only a subset of objectives. We assess the performance of reduced models varying in the number of objectives, the number of alternatives, the correlations among objectives, and attribute weights.

Recommended citation: Kusumastuti, S. A., & John, R. S. (2024). A simulation approach to investigate factors influencing the cost of omitted objectives in multiattribute models. Journal of Multi‐Criteria Decision Analysis, 31(1-2), e1826. https://doi.org/10.1002/mcda.1826

Charting the landscape of rail human factors and automation: A systematic scoping review

Published in Transportation Research Interdisciplinary Perspectives (Open Access), 2025

Abbreviated Abstract: This systematic scoping review examines research on human factors and automation in railways, with a focus on studies involving railway operators such as train drivers and traffic controllers. We explored six databases and solicited expert recommendations, identifying 65 relevant studies published since 2000. Studies were categorized based on methodology and analysed to identify key themes, measures, and research priorities. The review revealed five main types of studies: empirical simulations (32%), non-simulation studies (25%), literature reviews (8%), analysis of existing technologies (31%), and new technologies (20%). Key research priorities included assessing the impact of automation on operator performance, workload, and situational awareness. Human-in-the-loop simulations emerged as a crucial method for evaluating new automated systems. Nevertheless, gaps emerged, e.g., studies focus mainly on drivers, use small sample sizes, and pay little attention to operators’ communications.
Link to supplementary material: https://osf.io/3sxw7/files/osfstorage

Recommended citation: Kusumastuti, S. A., Kolkman, T. H., Lo, J. C., & Borsci, S. (2025). Charting the landscape of rail human factors and automation: A systematic scoping review. Transportation Research Interdisciplinary Perspectives, 30, 101350.

talks

teaching

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience

, , 1900

University of Twente

  • Tutorial Assistant
    • Data Analysis
    • Research Methodology and Descriptive Statistics
    • Technology, Organisation, and People
  • Guest Lecture
    • Smart Mobility - Human-AI teaming in mobility