Assistant Professor @UCDavis in Quant Psych
Discrete-/Continuous-Time Dynamic Networks and Community Detection
https://www.JonathanPark.dev
Jonathan J. Park
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A holiday gift from @suryadyutibaral.bsky.social for modeling longitudinal data in a non-parametric framework using continuous-time functional data analysis.
My work focuses on how we can identify and address undiagnosed heterogeneity in samples of heterogeneous time-series by drawing on techniques from graph theory and network analysis.
I also have a line of work directly in network analysis using cascading failure models and fuzzy clustering methods.
Wanted to announce that I will be recruiting graduate students this year in Quantitative Psychology here at UC Davis. If you are or know of any undergrads who are interested in dynamical systems and network analytic methods, please send them my way or get in touch!
I wouldn't have been able to complete this work without mentors and collaborators:
- Sy-Miin Chow
- Peter Molenaar
- @fishingwithzack.bsky.social
- Michael Hunter
- @chadshenkphd.bsky.social
- Michael Russell
In the paper, we highlight the strengths of modeling in continuous-time and contrast it with modeling in discrete-time dynamic networks.
We also highlight some key weaknesses in implementing an automated search of continuous-time dynamic networks RE: initial conditions and determining them sensibly
