Armun Liaghat

I am a theoretical evolutionary ecologist who uses mathematical, statistical, and computational tools to understand complex adaptive systems of interacting, replicating agents. A major part of my work is integrating ecology and evolution into a unified framework, which involves understanding the feedbacks between them across levels of organization, from genes to communities. Most of my study systems have been microbial communities and their lytic viruses. More generally, I study discrete, combinatorial phenotypes that determine the specificity of interactions.

Threads running through my work:

• Structure. Who interacts with whom, and how strongly, in communities of many species or agents, and how that network emerges from and drives functional output and evolution. Studied with various frameworks including the cavity method and random matrix theory.
• Memory & Learning. How records of past encounters, from immune memory to learned behavior, shape coevolution and adaptation, and how learned models can find structure in limited data.
• Control. Which species or inputs can steer a community toward a target output, and with which levers.

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