Assistant Professor
Syracuse University Department of Mechanical and Aerospace Engineering
Prof. Zigunov conducts research in the field of experimental aerodynamics at low- and high-Mach number regimes using state-of-the-art diagnostic tools and algorithms. Dr. Fernando Zigunov’s research is focused on leveraging automated experiments in fluid dynamics to deploy machine learning systems that can achieve tangible engineering goals to control various complex flow problems to develop and improve future aircraft and energy production systems. Dr. Zigunov also has extensive expertise in volumetric flow diagnostic techniques such as tomographic and scanning PIV, as well as time-resolved PSP, shadowgraph and schlieren. He is also interested in using data assimilation and modal analysis techniques to distill complex experimental data and understand its dynamical behavior.
Previous Experience:
Dr. Zigunov earned his PhD in Mechanical Engineering at Florida State University, USA and his B.S. in Mechanical Engineering at University of Vale do Rio dos Sinos, Brazil
. In his early career in Brazil, he spent seven years as a senior refrigeration engineer building large-scale refrigeration
plants for food processing. He pivoted to graduate studies in aerodyanmics based on his interest in fluid dynamics, which involved
application of advanced experimental techniques to examine and understand complex bluff body wakes. His research then moved towards
higher-speed flows such as shockwave-boundary layer interaction flows and control of supersonic jet noise. He then spent two years at the
Los Alamos National Laboratory building novel algorithms to perform three-dimensional, volumetric diagnostics in multi-fluid shock-turbulence
mixing flows of interest to nuclear fusion research. Currently, Dr. Zigunov leverages the various techniques and experiences learned throughout his career to develop novel diagnostics and methodologies in experimental high-speed aerodynamics, leading the Skytop Turbulence Laboratories at Syracuse University.
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