Mike Pereira

Researcher at Automatic Control

I am a postdoctoral researcher within the project STONE, which is carried out jointly by the Division of Applied Mathematics and Statistics in the Department of Mathematical Sciences and the Automatic Control Group within the Department of Electrical Engineering. The goal of the project is to use stochastic partial differential equations to model traffic flows and to estimate parameters based on data from real measurements.

My research areas are primarily spatial and computational statistics. But I also have strong interests in Machine Learning, graph theory and stochastic partial differential equations, and how these domains can foster new approaches to deal with spatial data.

Source: chalmers.se
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Showing 6 publications


Parameter and density estimation from real-world traffic data: A kinetic compartmental approach

Mike Pereira, Pinar Boyraz Baykas, Balázs Adam Kulcsár et al
Transportation Research Part B: Methodological. Vol. 155, p. 210-239
Journal article

Short-term traffic prediction using physics-aware neural networks

Mike Pereira, Annika Lang, Balázs Adam Kulcsár
Transportation Research, Part C: Emerging Technologies
Journal article

Traffic Reaction Model

Gyorgy Liptak, Mike Pereira, Balázs Adam Kulcsár et al

A matrix-free approach to geostatistical filtering

Mike Pereira, Nicolas Desassis, Cédric MAGNERON et al

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Showing 3 research projects


Learning in Stochastic Traffic Networks

Balázs Adam Kulcsár Automatic Control
Sondre Chanon Wiersdalen Automatic Control
Mike Pereira Automatic Control
Annika Lang Applied Mathematics and Statistics


Efficient approximation methods for random fields on manifolds

Annika Lang Applied Mathematics and Statistics
Erik Jansson Applied Mathematics and Statistics
Mike Pereira Automatic Control
Swedish Research Council (VR)


STOchastic Traffic NEtworks (STONE)

Annika Lang Applied Mathematics and Statistics
Balázs Adam Kulcsár Automatic Control
Pinar Boyraz Baykas Crash Analysis and Prevention
Mike Pereira Applied Mathematics and Statistics
Chalmers AI Research Centre (CHAIR)

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