Resources

In this PhD dissertation, Schmidt introduces optimization and simulation models to support the design and operation of resilient in-person election voting systems. Three core contributions: (1) a discrete-event simulation of pandemic-resilient polling-place design, with a case study of Milwaukee, WI; (2) the Polling Location Consolidation Problem (PLCP), an integer programming model applied to Richland County, SC; and (3) an optimization model for ballot drop box siting in Milwaukee.

In this PhD dissertation, Bernardo develops a simulation-based framework to examine how in-person election system conditions affect voter wait times and throughput. Three core contributions: (1) observational time studies of voting operations across multiple Rhode Island elections to calibrate arrival-rate and service-time parameters; (2) discrete-event simulation models of polling-place operations under varying equipment types, layouts, and resource levels; and (3) application of the models to COVID-19 social-distancing scenarios, precinct-consolidation decisions, and minimum requirements for accessible equipment.

Hostetter examines whether the use of electronic poll books affects voter wait times, finding mixed results that depend on context, including photo ID requirements and precinct demographics.

This research focuses on how the timing of voter file snapshots affects the most commonly cited advantage of voter file data: accurate measures of who votes.

This research uses difference-in-differences estimates that suggest that same day voter registration disproportionately increases turnout among individuals aged 18–24 (an effect between 3.1 and 7.3 percentage points).

This paper employs discrete-event simulation to model Milwaukee's in-person voting system during COVID-19. It reveals that poll worker shortages, social distancing measures, and PPE requirements can lead to very long voter wait times. The evaluation considers various design strategies to reduce pandemic-related effects, such as adding check-in locations, expanding early voting, and preventing the consolidation of polling sites.

This report examines poll workers in the current election environment, including recruitment challenges, training needs, and the role poll workers play in shaping the voter experience and in building public confidence in elections.

In this paper, authors analyze how transitioning to vote centers impacts voters' experiences, noting that inadequate implementation may result in longer waits and increased voter dissatisfaction.

This paper examines how changes in Election Day polling place locations affect voter turnout. The authors analyze voter behavior in three presidential elections in North Carolina (2008 - 2016), finding that these changes reduce Election Day voting on average, but that the reduction is offset by substitution into early voting.

In this paper, authors use snapshots of voter registration files (VRF) over time and machine learning models to test the effectiveness of unsupervised anomaly detection methods in detecting VRF modifications. They find that statistical models comparing administrative districts within a short time span and non-negative matrix factorization are most effective for surfacing anomalous events for review.

In this paper, authors explore how ballot length affects specific types of voting errors, including human-machine interaction errors and voter ballot-marking errors.

In this paper, authors match a high-quality, random sample of the U.S. population to multiple lists revealing that at least 11% of the adult citizenry is not on a voter list. An additional 12% is mislisted (i.e., not living at their recorded address).