Roberto Pereira

Ico_CTTC
Roberto Matheus Pinheiro Pereira | CTTC

Information and signal processing for intelligent communications (ISPIC)

Msc , Researcher (PR)

Phone: +34 93 645 29 00

Roberto Pereira received his M.Sc. degree in Informatics from the Technical University of Munich (Germany) in 2019 and Bachelors degree in Computer Science in 2014 from the Federal University of Maranhão (Brazil). Due to his research in the field accessibility on handwritten musical content using deep learning, he was awarded with the “Young Researcher Reward” by FAPEMA in 2014. Since then he has conducted numerous researches and deployed models in the fields of deep learning, computer vision, electrical signals, NLP, dimensionality reduction and wireless communication.

Currently, Roberto Pereira is a Marie Sk?odowska-Curie fellow ESR working on a European Training Network (ETN) project called Windmill. The network consists of a consortium of leading international research institutes and companies with experts in wireless communications and machine learning. The project itself aims at developing new network management and optimization tools based on machine learning.

As an Early Stage Researcher, Roberto’s role in the Windmill project is to analyze and synthesize machine learning solutions in large dimensional settings. Thus, he is focused on dimensionality reduction methods, unsupervised learning algorithms, smart agents and large optimization scenarios.

No results found
CLUSTERING COMPLEX SUBSPACES IN LARGE DIMENSIONS
2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL II, PROCEEDINGS: SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING SIGNAL PROCESSING THEORY AND METHODS. Vol 2022-May. pp. 5712-5716 January 2022.
Pereira R., Mestre X., Gregoratti D.
10.1109/ICASSP43922.2022.9747627 Google Scholar
ASYMPTOTIC SPECTRAL BEHAVIOR OF KERNEL MATRICES IN COMPLEX VALUED OBSERVATIONS
2021 Ieee Data Science And Learning Workshop (dslw). January 2021.
Mestre, X, Pereira, R, Gregoratti, D, IEEE
Google Scholar
Subspace Based Hierarchical Channel Clustering in Massive MIMO
2021 Ieee Globecom Workshops, Gc Wkshps 2021 - Proceedings. January 2021.
Pereira R., Mestre X., Gregoratti D.
10.1109/GCWkshps52748.2021.9682075 Google Scholar
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