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Hanno Hildenbrandt is a leading computational biologist whose work illuminates the hidden rules behind collective animal behavior, particularly in bird flocks. His research focuses on how complex group patterns—such as collective turns, splits, and escapes—emerge from simple, local interactions among individuals, a process known as self-organization. Hildenbrandt’s major contributions include developing and refining computational models that simulate these dynamics, allowing researchers to test hypotheses about behavioral rules that are difficult to observe directly in nature. His most influential work, "Self-organization of collective escape in pigeon flocks" (2022), has garnered 68 citations, demonstrating its impact on the field. A follow-up study on splits and collective turns under predation (2022, 47 citations) further cemented his reputation. More recently, his 2024 study on European starlings, "Towards a mechanistic understanding of collective escape," combines video footage with modeling to disentangle how large flocks change shape and structure when hunted. Hildenbrandt’s research is essential reading for anyone interested in the intersection of animal behavior, complex systems, and computational biology.