BI0S - Brazilian Institute of Data Science

• Grant number: 20/09838-0
• Support Opportunities: Research Grants - Research Centers in Engineering Program
• Duration: September 01, 2021 - August 31, 2026
• Field of knowledge: Interdisciplinary Subjects
• Convênio/Acordo: MCTI/MC
• Principal Investigator: João Marcos Travassos Romano
• Grantee: João Marcos Travassos Romano
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Host Company: Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação (FEEC)
• City: Campinas
• Partner institutions: UNIDADE NAO MAPEADA
• Pesquisadores principais: Alexandre Gori Maia ; Álvaro de Oliveira D'Antona ; Claudia Regina Castellanos Pfeiffer ; Henrique Nogueira de Sá Earp ; Jorge Moreira de Souza ; Jurandir Zullo Junior ; Konradin Metze ; Leonardo Tomazeli Duarte ; Niro Higuchi ; Peter Sussner ; Renato Machado ; Ricardo Suyama ; Romis Ribeiro de Faissol Attux ; Rosangela Ballini ; Sueli Irene Rodrigues Costa
• Associated researchers: Alberto Paradisi ; Aline de Oliveira Neves Panazio ; Ana Paula Romani ; André Kazuo Takahata ; Andrei Carvalho Sposito ; Angel Pontin Garcia ; Barbara Janet Teruel Mederos ; Benilton de Sá Carvalho ; Bruno Sanches Masiero ; Carlos Alberto Oliveira de Freitas ; Celsa da Silva Moura Souza ; Cesar Cabello dos Santos ; Claudio José Bordin Júnior ; Cristiano Torezzan ; Daniel Albiero ; Denis Gustavo Fantinato ; Diego Jair Vicentin ; Edson Amaro Junior ; Eduardo Alves Do Valle Junior ; Erich Vinicius de Paula ; Estevão Esmi Laureano ; Eulanda Miranda Santos ; Fábio Maia Bertato ; Felix Dieter Antreich ; Filipe de Oliveira Costa ; Filipe Ieda Fazanaro ; Giovanni Moura de Holanda ; Gleyce Kelly Dantas Araújo Figueiredo ; Guilherme Palermo Coelho ; Harki Tanaka ; Hugo Enrique Hernández Figueroa ; Igor Gadelha Pereira ; Ivette Raymunda Luna Huamaní ; Joao Batista Florindo ; João Frederico da Costa Azevedo Meyer ; João Marcos Bastos Cavalcanti ; João Paulo Dias de Souza ; José Guilherme Cecatti ; José Luiz de Souza Pio ; Juan Gabriel Colonna ; Júlio César Teixeira ; Kelson Mota Teixeira de Oliveira ; Kenji Nose Filho ; Leandro Russovski Tessler ; Leonardo Abdala Elias ; Leonardo Henrique de Melo Leite ; Levy Boccato ; Lucas Carvalho Cordeiro ; Luís Otávio Zanatta Sarian ; Luiz Henrique Antunes Rodrigues ; Manish Sharma ; Marcelo da Silva Pinho ; Marcelo Gomes da Silva Bruno ; Marcelo Pereira da Cunha ; Marcos Augusto Bastos Dias ; Marcos Nakamura Pereira ; Marcos Ricardo Omena de Albuquerque Maximo ; Marcos Vanine Portilho de Nader ; Marcus Henrique Victor Júnior ; Maria Gorete Valus ; Maria Letícia Cintra ; Mônica Mitiko Soares Matsumoto ; Murilo Bellezoni Loiola ; Paula Dornhofer Paro Costa ; Priscila Cristina Berbert Rampazzo ; Priscila Pereira Coltri ; Priscyla Waleska Targino de Azevedo Simões ; Rafael Ferrari ; Raimundo da Silva Barreto ; Renata Pelissari Infante ; Renata Ribeiro Do Valle Gonçalves ; Renato da Rocha Lopes ; Renato Passini Júnior ; Rodolfo de Carvalho Pacagnella ; Rodrigo Lanna Franco da Silveira ; Rosa Maria Soares Madeira Domingues ; Rosiane de Freitas Rodrigues ; Sandra Eliza Fontes de Avila ; Sergio San Juan Dertkigil ; Simone Pallone de Figueiredo ; Sophie Françoise Mauricette Derchain ; Tiago Fernandes Tavares ; Vandermi João da Silva ; Victor Mendonca de Azevedo ; Washington Alves de Oliveira ; Weiler Alves Finamore
• Associated grant(s): 22/14386-7 - Sum Product Algorithm for Machine Learning, AV.BR; 22/05230-3 - 2022 North American Fuzzy Information Processing Society Conference NAFIPS'2022, AR.EXT
• Associated scholarship(s): 22/00196-1 - Fuzzy differential equations with interactive derivatives on time scales, BP.PD

Abstract

The Brazilian Institute of Data Science (BI0S) is a research center with the main purpose to develop state-of-the-art solutions in data science and artificial intelligence (AI), solving relevant problems and connecting academia, companies, startups, society and the public sector in an integrated innovation ecosystem. It will contribute to scientific, technological and social development, addressing problems that originate in multi-stakeholder interactions. Moreover, BI0S will foster entrepreneurship and startup culture, which will help bring its ideas to the market. It will also promote initiatives for the dissemination of knowledge on data science and AI, aiming at attracting young talents from high school and early college years, as well as providing continuous education opportunities for professionals. At first, BI0S will focus on two strategic areas: Health and Agriculture. On the Health track, BI0S will tackle problems associated with the health of women at various age groups. The main questions are related to maternal and neonatal death and the early mortality of women due to preventable and potentially curable diseases, such as colon and breast cancer. Other problems of interest include the development of AI tools for medical diagnostics and drug development. On the Agro trail, the main objective is to increase the availability and quality of information to assist decision making at various levels. At the local level of individual farmers, BI0S will develop solutions for precision agriculture. At regional and global scales, BI0S will address central problems such as the impacts of climate change on national agriculture. BI0S will also develop AI methods applied to resource optimization and productivity gains, along with industry-environment sustainable integration. In addition to the Health and Agro tracks, BI0S has a Method track that supports the Health and Agro applications with state-of-the-art and novel tools from artificial intelligence. Finally, BI0S will leverage its members' expertise towards transversal problems of great interest, which lie at the interface between the Health and Agro tracks, eg. the relations between a given farming strategy and its effects on human health. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

R. S. OLIVEIRA; C. T. L. S. GHIDINI; C. TOREZZAN; W. A. OLIVEIRA. Modelagem para o Problema de Roteamento de Veículos Fretados. Trends in Computational and Applied Mathematics, v. 23, n. 4, p. 801-828, 2022-11-14. (20/09838-0)

FLORINDO, JOAO; METZE, KONRADIN. Using Non-Additive Entropy to Enhance Convolutional Neural Features for Texture Recognition. Entropy, v. 23, n. 10, OCT 2021. (20/01984-8, 20/09838-0)

SUSSNER, PETER; CARO CONTRERAS, DAVID ERNESTO. Generalized morphological components based on interval descriptors and n-ary aggregation functions. INFORMATION SCIENCES, v. 583, p. 14-32, JAN 2022. (18/13657-1, 20/09838-0)