JasmineMcKenzie

PhD Student - Human Centered Computing

Jasmine
mckenzie

 
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About Me

Research Interests:

My current research interest involves accessing health equity and contributing to a Culture of Health to effect change in marginalized and underrepresented communities. Specifically, I’m studying technological health literacy interventions for the Black community backed by public health and health education theories and frameworks. I aim to identify the need for community-specific measures such as determining community needs, involving stakeholders, building trust, and understanding learning styles before creating health literacy interventions for the Black community. In the future, I would like to pivot to utilizing technology for patient-centered care. I would like to specifically focus on teaching Black women about common pregnancy risks since this population is 3x-4x more likely to experience fatal pregnancy complications. Because trust is also a factor that plays a part in these complications, using culturally relevant virtual agents or mobile applications would be ideal for this population. I believe that fundamental knowledge and trust are the foundation to long-lasting health equity in marginalized communities.

Experience

Pacific Northwest National Laboratory                                                     May 2023-July 2023

Visiting Researcher                                                                                      Gainesville, Florida

Trust in Generative Language Models Literature Review Paper

  • Surveyed common trust violations between Human-AI teams, specifically when using generative language models in the workplace.

  • Examined the techniques used to mitigate and restore trust to improve reliance on generative language models in Human-AI teams.

The Effect of Expert Explanation on the Ability to Predict Machine Learning Performance

  • Designed a within-subjects study focused on evaluating the effects of expert derived confidence scores and expert derived verbal explanations on people’s overall understanding of a ML classifier’s performance.

  • Developed a survey to determine if expert derived verbal explanations were more effective at helping electrical grid operators predict the classifiers performance than expert derived confidence scores.

Computing for Social Good Lab                                                       August 2021–Present

Research Assistant                                                                                          Gainesville, Florida

Improving Health Literacy in the Black Community with Technology: A Narrative Review

  • Conducted a comprehensive review of technological interventions aimed at improving health literacy, resulting in a paper analyzing the success and backing of the interventions and end-user involvement.

  • Identified the need for community-specific measures such as determining community needs, involving stakeholders, building trust, and understanding learning styles before creating health literacy interventions for the black community.

  • Discovered that conversational agents and mobile apps were popular intervention methods in the studies reviewed, with potential for use in the black community.

Voter Verification using Facial Recognition Verification

  • Implementing facial recognition verification software to improve the voter verification process at the polls to improve accuracy when compared to traditional methods.

  • Utilizing Amazon's AWS Compare Faces software to measure the similarity between individuals accurately.

  • Conducting a wizard of oz study using actors as voters and real poll workers to determine the accuracy of the poll workers' choices in verifying eligible voters.

Pacific Northwest National Laboratory                                                        May 2021–July 2021

PhD GEM Intern                                                                                               Richland, Washington

The Risk of Cybersecurity Threats and Vulnerabilities in Healthcare

  • Surveyed cybersecurity threats and vulnerabilities in medical institutions and implantable medical devices, providing insights for risk reduction.

  • Developed a plan for reducing the risk of cyberattacks in healthcare, requiring collaboration across multiple stakeholders.

  • Investigated the impact of basic cybersecurity education and training on healthcare workers' ability to detect potential cybersecurity risks.

  • Contributed to the creation of a safer and more secure healthcare environment through the understanding of cybersecurity risks and the development of mitigation strategies.

research Interest

Human-Centered Computing

Health Literacy

Pregnancy Education

CS Education

Culturally Relevant Computing

 

Software

InVision
Adobe XD
Figma
Brackets
Unity
Android Studio
XCode

 

Skills

User Testing
Mockups
Quantitative Research

Qualitative Research
Low-Fidelity Prototyping
High-Fidelity Prototyping

 

Programming languages

Java
C++
Python
JavaScript
HTML/CSS