Welcome! I'm a PhD candidate at the University of Michigan.
My research interests fall in linguistics, computer science, and the study of mind. I primarily use computational models and experimental studies—in tandem—to study the algorithms and representations humans use to learn phonological alternations.
I also research how contributions to our understanding of human learners can improve natural language processing.
Prior research has contributed methods for choosing unlinked pairs of nodes to investigate further with a link prediction method or experimental study, identifying subtle patterns in networks that are too infrequent to be discovered by frequency alone, and for discovering errors and missing information in incomplete knowledge graphs. Applications of this work include anomaly detection, suspicious behavior discovery, and city/urban planning, including projects with the City of Detroit on transportation planning.
I am grateful to have been selected for 2020-2023 NSF GRF and NDSEG fellowships. I am currently funded by the NSF GRF.
Feel free to contact me at firstname.lastname@example.org.
In case you are wondering, the name of this website ("quickshift") is a nod to my life-long love of road trips, driving, and cars in general.