Christensen uses network and data science to model dynamical systems in psychology. He views psychological phenotypes as dynamic complex systems: dynamic meaning they change across time and complex meaning the interaction between their components and other systems are often difficult to discern.

Broadly, his work aims to develop dynamic network science tools that capture person-specific variation that can be used to make more accurate measurements (e.g., how depression is quantified) and predictions (e.g., whether someone will become depressed) as well as make better generalizations to broader populations to uncover underlying mechanisms that govern human behavior. These tools are accented by data science techniques such as natural language processing to develop more idiosyncratic representations of who people are.

You can visit his university webpage here.

You can visit his personal webpage here.

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