Sérgio Pequito at the Priberam Machine Learning Lunch Seminar

Date:Tuesday, May 12th, 2015 at 1pm (Lunch will be provided)
Venue:Anfiteatro do Complexo Interdisciplinar, IST Alameda, Lisbon
url: http://labs.priberam.com/Academia-Partnerships/Seminars.aspx 

Minimum Number of Probes for Brain Dynamics Observability

Abstract:

In this talk, we address the problem of placing sensor probes in the brain such that the system dynamics’ are generically observable. The system dynamics whose states can encode for instance the fire-rating of the neurons or their ensemble following a neural-topological (structural) approach, and the sensors are assumed to be dedicated, i.e., can only measure a state at each time. Even though the mathematical description of brain dynamics is (yet) to be discovered, we build on its observed characteristics and assume that the a good model of the brain activity satisfies fractional-order dynamics.

Although the sensor placement explored in this talk is particularly considering the observability of brain dynamics, the proposed methodology applies to place the minimum number of dedicated sensors to ensure generic observability in discrete-time fractional-order systems for a specified finite interval of time. Finally, an illustrative example of the main results is provided using electroencephalogram (EEG) data.

Sérgio Pequito is currently a postdoctoral researcher at University of Pennsylvania. His research consists in understanding the global qualitative behavior of large scale systems from their structural or parametric descriptions and provide a rigorous framework for the design, analysis, optimization and control of large scale (real-world) systems.He graduated from the Electrical and Computer Engineering dual degree from the Carnegie Mellon Portugal Program, receiving degrees from both Carnegie Mellon University and Instituto Superior Técnico. Furthermore, he received his BSc and MSc in Applied Mathematics from the Instituto Superior Técnico.   

Sérgio Pequito was awarded with the best student paper finalist in the Conference on Decision and Control 2009, the ECE Outstanding Teaching Assistant Award at Carnegie Mellon University, and the Carnegie Mellon Graduate Teaching Award (university-wide) honorable mention, both in 2012.