Authors

**Guy Y. Cornejo Maceda** is a postdoctoral researcher at Harbin Institute of Technology at Shenzhen, working on turbulence control with machine learning methods for a fast learning of robust, feedback control laws and their visualization. He obtained his Ph.D. in 2021 at Paris-Saclay University (France) under the supervision of Profs. Bernd R. Noack and François Lusseyran with whom he accelerated the learning of feedback control laws by a factor 10 compared to previously employed machine learning control. His methodology has been demonstrated on numerical and experimental MIMO plants. Examples include drag reduction and stabilization of the fluidic pinball, stabilization of the open cavity flow, lift increase and drag reduction of a high-Reynolds number airfoil, drag reduction and side-force mitigation of a yawed truck model and even the challenging feedback smart-skin separation control over a smooth ramp with 30 actuators and 56 sensors.

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**François Lusseyran** is currently Emeritus Research Director at the CNRS in a laboratory of Paris-Saclay University, LISN (France). His career as a fluid mechanics experimentalist has always followed the thread of the expression of nonlinearities in the space-time dynamics of various flow contexts. This began with the creation of vortex circulation at the Max Planck Institut für Strömungsforschung in 1978 in Göttingen (Germany) and now contributes to the control of vortex structures, developing in wakes and resonant flows, by searching for control laws with the help of machine learning algorithms. Other research topics have included, for example, the dynamic relationship between the heart and its arterial system (LMFE Orsay-Paris, France), transitions between gas-liquid two-phase flow regimes (LEMTA, Nancy, France, University of Illinois – Urbana-Champaign, USA), model reduction in turbine mixers and in jets with transverse flow (LEMTA, Helixor, Rosenfeld, Germany) dynamics of open cavities in incompressible regime and moderate Reynolds numbers (LISN ex-LIMSI – LFD, FIUBA-UBA, Buenos Aires, Argentina), many years of collaboration on metrological issues and data analysis (IPPT PAN, Warsaw, Poland) and reduction of temporal dynamics forced by the so-called coherent structures (CORIA, Rouen, France – LFD – LadHyX, Palaiseau, France).

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**Bernd R. Noack** is National Talent Professor at the Harbin Institute of Technology, Shenzhen, and Honorary Professor and Chair of Turbulence Control at TU Berlin. Until 2020, he was Research Director CNRS at LIMSI, Paris-Saclay and Professor at TU Braunschweig and TU Berlin. Past affiliations include the United Technologies Research Center, Max-Planck Society, German Aerospace Center and University of Göttingen. He develops closed-loop turbulence control solutions for cars, airplanes and transport systems in an interdisciplinary effort with leading groups in China, Europe and USA/Canada. His team is advancing the frontiers of nonlinear control-oriented reduced-order models and machine learning control, an automated learning of control laws in experiment and simulation. He has co-authored over 250 refereed publications, including 2 patents, 2 textbooks, 3 other books, 3 review articles and over 120 international journal articles. His work has been honored by numerous awards, e.g., a Fellowship of the American Physical Society, a CNRS Scientific Excellence award, a Senior ANR Chair of Excellence in France, and the von Mises Award of International Association of Applied Mathematics and Mechanics. He is awarded outstanding faculty at HIT and a highly cited researcher (top 1% in Mendeley/Stanford list).

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