The Latin American Workshop on Information Fusion

Federal University of Rio de Janeiro - Brazil

(Hybrid)

November 23th, 2023

The First Latin American Workshop on Information Fusion (LAFUSION 2023) is a workshop focusing on the latest research results on the Information Fusion in Latin America. The goal of this workshop is to create a community of Information Fusion researchers in Latin America. Accepted papers will be published in IEEE. Authors of accepted papers are expected to present their work in a plenary session as part of the main workshop program. Proceedings will be indexed in the IEEE Digital Library, SCOPUS, and other prominent digital libraries.

Information fusion is a multidisciplinary field that focuses on combining and integrating information from diverse sources to improve the accuracy, completeness, and reliability of the resulting information. It involves the process of merging data or knowledge from multiple sensors, databases, or information systems to generate a unified and coherent representation of the underlying reality.

The main goal of information fusion is to extract meaningful and actionable insights by leveraging the strengths of individual information sources while compensating for their limitations, uncertainties, or redundancies. It aims to provide a more comprehensive and accurate understanding of a given situation or phenomenon than what can be achieved by using individual sources in isolation.

Information fusion techniques typically involve various processes, including data preprocessing, feature extraction, data association, probabilistic modeling, decision-making, and knowledge representation. These processes may utilize methods from diverse disciplines such as statistics, signal processing, pattern recognition, artificial intelligence, machine learning, and cognitive science.

Applications of information fusion are widespread and can be found in fields such as surveillance and intelligence, remote sensing, robotics, autonomous systems, medical diagnosis, weather forecasting, transportation systems, and cybersecurity. By integrating and interpreting information from multiple sources, information fusion enables improved situational awareness, decision-making, and prediction capabilities, leading to enhanced performance, efficiency, and reliability in complex and uncertain environments. Several Latin American problems could be solved by Information Fusion. We are looking to form a Forum to debate the usage of Information Fusion to produce solutions for the challenges in the region.

ADDRESSES

VENUE

Av. Athos da Silveira Ramos, 149 - Bloco G, Sala 122 - Cidade Universitária da Universidade Federal do Rio de Janeiro, Rio de Janeiro - RJ, 21941-909, Brasil

PROGRAM

TOPICS OF INTEREST

Probability theory, Bayesian inference, argumentation, Dempster-Shafer theory, possibility and fuzzy set theory, rough sets, logic fusion, preference aggregation, decision theory, random sets, finite point processes and others.

IMPORTANT DATES

PAPER SUBMISSION
October 22th, 2023
ACCEPTANCE NOTICE
November 9th, 2023
CAMERA READY SUBMISSION
November 17th, 2023
WORKSHOP DATE
November 23th, 2023

ORGANIZATION

GENERAL CHAIRS

Paulo Costa

George Mason University

USA

Claudio Miceli de Farias

Federal University of Rio de Janeiro

Brazil

TECHNICAL PROGRAM COMMITTEE

Alan Sá

Universidade de Lisboa

Portugal

André Braga

EMBRAER S.A

Brazil

Anne-Laure Jousselme

CS Group

France

Beatriz Azevedo

Polytechnic Institute of Bragança

Portugal

Carolina Marcelino

Federal University of Rio de Janeiro

Brazil

Chee-Yee Chong

Independent consultant

USA

Edgar Sarmiento

Universidad Nacional de San Agustin de Arequipa

Peru

Eduardo Hargreaves

Petrobrás

Brazil

Fabrício Faria

Federal University of Rio de Janeiro

Brazil

Flavia Delicato

Fluminese Federal University

Brazil

Gabriel Mattos

Universidad de Alcalá

Spain

Guilherme Horta Travassos

Federal University of Rio de Janeiro

Brazil

Henrique Gasparotto

ISEN

France

Jose Brancalion

EMBRAER S.A

Brazil

Juliana França

Federal University of Rio de Janeiro

Brazil

Kathryn Laskey

George Mason University

USA

Lance Kaplan

Army Research Laboratory

USA

Lauro Snidaro

University of Udine

Italy

Leandro Santiago de Araújo

Fluminense Federal University

Brazil

Leopoldo Lusquino Filho

São Paulo State University

Brazil

Luidi Simonetti

Federal University of Rio de Janeiro

Brazil

Luis Arenas

São Paulo State University

Brazil

Marcelo Martins de Sena

Federal University of Minas Gerais

Brazil

Pablo Rangel

Brazilian Navy

Brazil

Pedro Henrique González

Federal University of Rio de Janeiro

Brazil

Silas Lima Filho

Federal University of Rio de Janeiro

Brazil

Vivian Santos

Federal University of Rio de Janeiro

Brazil

SUPPORT