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EE Graduate Seminar: Bridging data-driven and physical model-based methods for health monitoring

Start Date: November 11, 2018
End Date: November 11, 2018

By Professor Meriem Laleg (KAUST)

In the last twenty years, there has been a growing interest in developing and implementing health monitoring and diagnosis methods. Traditional approaches are based on physical models combined with effective estimation algorithms. Though these approaches have shown a considerable success in many biomedical monitoring applications, nowadays with advances in sensors technology and computational capabilities a shift towards data-driven models and algorithms has surfaced. In addition, the interest in integrating both approaches to improve diagnostic systems has grown providing new reliable, accurate, fast and robust solutions for health monitoring. In this talk, I will give an overview of my research group’s activities in the development of accurate models and efficient model-based based and data-driven methods and algorithms for monitoring biomedical systems.  I will illustrate the impact of our proposed methodologies through several applications. ​

Biography: Meriem Laleg is an associate professor in the division of Computer, Electrical and Mathematical Sciences and Engineering at KAUST and 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 PhD 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 was elevated to an IEEE senior member in 2015. She won the best paper awards with her students at the IEEE International Conference of the IEEE Engineering in Medicine and Biology Society and the IEEE International Conference on Control Engineering and Information Technology. She has been recently recognized for being among the three finalists in the academic of distinction category (engineering) of the leadership excellence for women awards. She is also member of the steering committee of KAUST women in data science and a KAUST ambassador for women in data science.

More Information:

For more info contact: Prof. Taous Meriem LALEG-KIRATI: email:
Date: Sunday 11th Nov 2018
Time:12:00 PM - 01:00 PM
Location: Bldg.9, Level 2, Hall 1
Refreshments: light lunch will be served at 11:45