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
Minimum Number of Probes for Brain Dynamics Observability
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.