Cao, prof. dr. ir. Ming
Ming Cao is hoogleraar Netwerken en Robots aan de Faculty of Science and Engineering. In zijn onderzoek richt hij zich op multi-agent systems, complexe systemen en netwerken, sensornetwerken en autonome robots. Cao verricht baanbrekend werk op het gebied van controlesystemen die groepen autonome robots laten samenwerken. Om autonome auto’s en robots veilig en effectief te laten functioneren, moeten zij rekening houden met elkaars handelen. Ming Cao werkt aan deze ontwikkeling met collega’s uit de sociologie, wiskunde en biologie. Op deze manier ontwikkelt hij algoritmen voor de robots die deels geïnspireerd zijn op de bewegingen van dieren, vooral vissen en vogels die ook in formatie handelen. Ming Cao is verder benoemd tot directeur van de Jantina Tammes School of Digital Society, Technology and AI, het interdisciplinaire platform gericht op digitale innovatie, kunstmatige intelligentie en technologische vooruitgang.
Research Minute Young Academy Groningen - Ming Cao
Cao behaalde in 1999 zijn Bachelor of Engineering aan de Tsinghua University in Peking, China. Vervolgens behaalde hij in 2002 zijn Master of Engineering aan dezelfde universiteit. In 2003 behaalde hij daarnaast zijn Master of Science aan Yale University in New Haven, Verenigde Staten en in 2007 ontving hij zijn PhD bij het Department of Electrical Engineering van Yale University. In 2023 ontving Cao een Vici-beurs voor zijn onderzoek naar besluitvorming van autonome robots.
Eerder in het nieuws
2024
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Ramazi,
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concurrent targeting for planar arrays of point sources.
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B. B., Zhang, H. T., Yao, W., Sun, Z., &
Cao, M. (2024). Coordinated Guiding Vector Field
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69(7), 4805-4812. https://doi.org/10.1109/TAC.2024.3355321
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& Cao, M. (2024). Discrete-time layered-network
epidemics model with time-varying transition rates and multiple
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Zhang,
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(2024). Distributed online constrained convex optimization
with event-triggered communication. European
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publication. https://doi.org/10.1016/j.ejcon.2024.101042
Wang,
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Update Rules on Regular Networks. IEEE
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of general linear systems: An adaptive gain scheduling
strategy. Automatica, 161,
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M., Rauws, W., & Bolderdijk, J.
W. (2024). Overcoming inaction: An agent-based
modelling study of social interventions that promote systematic
pro-environmental change. Journal of Environmental
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Recent Developments of Subsurface Small-Leak Detection
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(2024). Tightening Poincaré–Bendixson theory after
counting separately the fixed points on the boundary and interior
of a planar region. Electronic Journal of
Qualitative Theory of Differential Equations,
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Ong,
L., Cao, M., Verkerke, G.
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position detection during seated office work. In 2024
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Social Cognitive and Affective Neuroscience,
19(1), Article e017. https://doi.org/10.1093/scan/nsae017
2023
Zhang,
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Control, 69(5), 3278-3285. https://doi.org/10.1109/TAC.2023.3319549
Kamat,
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Actions and Opinions in Social Networks. IEEE
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(2023). Satellite Formation Flying Control by Using Only
Angle Measurements. IEEE Transactions on Aerospace
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for Multirobot Path Navigation Using Guiding Vector Fields.
IEEE Transactions on Robotics,
39(4), 2654-2668. https://doi.org/10.1109/TRO.2023.3266994
Venegas-Pineda,
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Yao,
W., Lin, B., Anderson, B. D. O., &
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Desired Path in Vector-Field Guided Path Following.
IEEE Transactions on Automatic Control,
68(11), 6812-6819. https://doi.org/10.1109/TAC.2023.3239431
2022
Su,
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Convergence Analysis of Dual Decomposition Algorithm in
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2021
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K., Zino, L., & Cao, M.
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infections accounting for behavior and control actions.
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Models and Lotka-Volterra Systems.
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