Fish Behavior Recognition and Data-driven Control for Smart Aquaculture

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In this talk, I will present our progress in controlling fish feeding and monitoring water quality in smart aquaculture systems. The idea consists of combining computer vision tools along with optimal control strategies.  I will first show some recent results on implementing reinforcement learning for optimal fish feeding and temperature monitoring. Then, I will discuss the implementation of computer vision tools as an essential component for analyzing fish behavior. I will conclude with some  algorithms for the synthesis of computer vision-based classifiers that enable control architectures.

Brief Biography

Meriem Laleg is an associate professor in the division of Computer, Electrical, and Mathematical Sciences and Engineering at KAUST and a member of the Computational Bioscience Research Center (CBRC). She joined KAUST in 2011 after being a postdoctoral fellow and a researcher at the French Institute for Research in Computer Sciences and Control Systems (INRIA) in Bordeaux.  She received her Ph.D. in Applied Mathematics in 2008 from INRIA and Versailles University. Professor Laleg’s work is in the general area of mathematical control theory, systems modeling, signal processing, and their applications.  Her primary research goals are directed towards developing effective estimation methods and algorithms to understand complex systems, extract hidden information, and design control and monitoring strategies. Her research projects are motivated by real-world problems in engineering and biomedical fields. She is an IEEE senior member, a member of the IEEE Control Conference Editorial Board, an associate editor of the IEEE access Journal and several control conferences including the European Control Conference. She is also a member of the international federation of automatic control (IFAC) technical committee on Biological and Medical Systems (TC8.2) and Modeling and Control of Environmental Systems (TC8.3)

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