Analyzing Human trust of automated vehicles
This research was completed May-Aug 2021 in order to model human trust of self-driving vehicles through carefully designed experiments, and draw conclusions from the data collected. As a result, two separate studies (one online and one in-person) had already been conducted to determine how individuals reacted to engaging with an autonomous vehicle and how their trust developed, sustained, or regressed over time.
Artificial Intelligence:
Evaluating the Influence of Environmental Factors on the Spread of COVID-19
This project was conducted in Summer 2020 during the ongoing coronavirus pandemic. An Artificial Neural Network (ANN) was designed and developed to understand the COVID-19 virus through an environmental lens by analyzing big data regarding case logistics and environmental considerations.
Difficulties encountered included collecting and cleaning relevant data, and accounting for confounding factors due to lack of isolating environmental effects.
Collaborative findings: https://youtu.be/4O5q6-Mh1wE
Human Centered Design considerations within the medical space
We performed anthropometric analyses of a Patient and Provider facing monitor utilized in medical environments and hospital settings.