Max Jerdee has joined the Santa Fe Institute (SFI) as a Complexity Postdoctoral Fellow. His research centers on developing statistical tools to analyze the structure of networks across different systems. According to Jerdee, “There are many different networks we could consider. Networks of friendship, networks in your brain, networks of transportation … and somehow you can come up with a unified language to talk about all these things.” He aims to create mathematical and statistical methods that reveal patterns in complex systems.
Jerdee's work emphasizes building interpretable and unbiased methods for network data analysis. He uses Bayesian inference and other probabilistic techniques to develop models that can identify network structures while rigorously quantifying uncertainty. He notes, “I think a lot about how our methods shape what we believe we see in data. If the instrument is biased, everything downstream will be too.”
Recently, Jerdee has compared systems with varying degrees of hierarchy, such as hierarchical animal dominance networks and more balanced outcomes in sports leagues. His research demonstrates that the same mathematical framework can describe both types of systems.
At SFI, Jerdee plans to broaden these tools into a comprehensive framework for comparing network organization and exploring the mechanisms behind their formation. He is also working on algorithmic improvements using techniques from statistical physics to make these models more efficient and scalable. This could allow researchers to study how structure and function coevolve in complex systems at larger scales.
