I am interested in understanding the underlying dynamics of complex real-world systems. My research tends to focus on methods for automating data science in order to achieve this. Basically I would like my computer to do my job for me; that includes tasks such as cleaning data, engineering features, writing code, and explaining scientific results. I am interested in applying my work in areas that improve social good.
I’m currently a postdoctoral researcher at University of Pennsylvania. I work in the Computational Genetics Lab, which is part of the Institute for Biomedical Informatics. This group is dedicated to identifying the genetic and environmental factors that contribute to human disease.
Recently I received a Pathway to Independence Award from the NIH. I’m using this award to study methods for interpretable representation learning from electronic health records. I’m also using it to dive deeper into the world of biomedical informatics.
Before Penn, I applied most of my research to wind energy, including identification and control of wind turbine dynamics and gearbox reliability.
- Computational Genetics Lab in the Institute for Biomedical Informatics
- Warren Center for Network and Data Sciences
- Hampshire Computational Intelligence Laboratory (Lee Spector’s research group)
- UMass NSF Wind Energy IGERT program (my PhD fellowship)
- National Wind Technology Center (NWTC)
- NWTC Gearbox Reliability Collaborative
- Penn AI: Accessible, Automatic Data Science
- Symbolic Representation Learning
- Lexicase Selection
- Improving Machine Learning Standards in Biomedical Informatics
- Predicting Patient Outcomes with Electronic Health Records
- Identifying Concise, Nonlinear Dynamic Models
- Structural Adaptation of Models and Controllers