Hello! I'm Caleb, a PhD student at the University of Michigan, where
I work with Danai Koutra.
Some of my interests are streaming algorithms, graph summarization, information theory, and philosophy.
My current projects are on identifying inductive patterns—those that generalize beyond the data they were identified in. These may be patterns that extend beyond the boundaries of an incomplete knowledge graph, or patterns that reoccur in a graph edge stream, even in the presence of concept drift. The methods I work on draw on ideas from information theory and cognitive science.
Pervious projects I have worked on involved representation learning to capture high-order (non-Markovian) dependencies in network trajectories, identifying categories of influencers in social movements, and predicting protein binding sites.
Underlying all my work, I try my best to think critically about its implications. Right now, there are at least a couple fundamental questions that I especially wrestle with:
1) What might be the implications of methods I work on? Will they be constructive or destructive to society?
2) What is the motive of my research?
3) Does my research methodology match my motive?
A current musing: are flocks of birds Turing Complete?
Prior to Michigan, I received a B.Sc. in Computer Science from Purdue University, where I was fortunate to work with Jennifer Neville, Dan Goldwasser, and Daisuke Kihara.
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.