Kyle Baacke
Graduate Students
Email: ude.sionilli@2ekcaabk
Research Interests
- Decision Making
- Computational Neuroscience
- Moral Judgment
- Machine learning
Research Description
Advancements in preprocessing and analytical methods for neuroimaging data have seen sharp improvement over recent years, as have machine learning methods which can leverage the high dimensionality and multivariate structure of neuroimaging data. One common application is to generate predictions about behavior from neuroimaging data. What input features from neuroimaging can we compute that enable the most accurate and robust models? And what inferences about the functioning of the human brain can we draw from those meaningful features? I am involved in a variety of collaborations that seek to answer these questions with large-scale open-access datasets. Specifically, I have two collaborative projects aimed at evaluating the benefits of various experimental and analytical choices in using functional neuroimaging data in machine learning models.
In addition to evaluating models for neuroimaging data, I am working on a project that investigates how scarcity of resources might relate to moral judgment and decision-making.
I have a passion for programming and data management. I am always looking for ways to enable research efficiency, replicability, and scalability.
Education
I received a Bachelor of Arts degree in Psychology from Knox College in 2016 with a focus on addiction. Before enrolling at University of Illinois, I worked as a data systems analyst in the Cannabis retail industry, where I gained hands on management experience of cloud resources and various programming languages.
