projects and partners
Quantum Paradigms and Potential Applications to the Financial Market
2025-2025 | Inter / UFMG
This research project, funded by Banco Inter, focuses on quantum computing, quantum information, quantum communication. Its main goal is to explore the potential of quantum paradigms for solving complex, high-dimensional problems that are difficult to address with classical systems.
Intelligent System for Temperature Prediction in Ovens (SIPTV)
2025-2026 | Aço Cearense / UFMG
The project applies machine learning models to predict temperature in industrial ovens, learning from historical sensor data and operational parameters. By anticipating temperature fluctuations, it enables more efficient control, improves product quality, and reduces energy consumption. Several members of our group are participants in this project.
Geometric Methods for Graph Coloring and Partitioning
2025-... | FAPEMIG / UFMG
FAPEMIG Universal research project exploring algebraic combinatorics, semidefinite programming, and combinatorial optimization through geometric methods to tackle NP-hard graph partitioning and coloring problems, with applications to quantum information. It funds the PI’s group, currently including postdocs, PhD, MSc, and undergraduate students.
Artificial Intelligence in the Context of Graphs
2025-2026 | MPMG / UFMG
Use of large-scale networks and graph mining algorithms for behavioral pattern analysis. Several members of our group are participants in this project.
Algebraic Combinatorics and Semidefinite Optimization: Interfaces and Applications to Quantum Computing
2024-2027 | CNPq / UFMG
This project explores the interface of algebraic combinatorics, semidefinite optimization, and quantum computing, using graphs as the key mathematical model for system interactions. Its goal is to support extended research visits of PhD studentds to the University of Waterloo.
Graph Spectrum and Quantum Models of Clustering
2023-2026 | FAPEMIG / UFMG
Project funded by FAPEMIG’s Call 015/2022 – Special Visiting Researcher, fostering collaboration between the local research group and Professor Aida Abiad from Eindhoven University of Technology. It focuses on spectral methods applied to clustering problems in graphs and includes funding for a postdoctoral researcher as well as exchange visits between the local group and the Netherlands.
Graphs’ Spectrum, Quantum Information, and Conic Optimization
2023-2026 | CNPq / Gabriel Coutinho
This project explores the relationship between graph combinatorics and spectral properties in modeling quantum systems, where such interactions shape quantum phenomena and state behaviors. It also investigates the use of conic optimization techniques to study these connections.
Deep Learning of Geological Surfaces for Offshore Reservoir Prospecting
2022-2025 | CNPq / UFMG
The project builds deep-learning models that fuse noisy, high-resolution well logs with resilient but incomplete seismic data to improve cyclostratigraphic interpretation, facies stacking, and elastic-inversion–based reservoir characterization for offshore exploration. It aligns with the ongoing PetroIaGeo collaboration (UFMG–Petrobras, since 2021) and leverages supervised learning on geological signals to enhance explainability and accuracy. Several members of our group are participants in this project.
Artificial Intelligence Applied to Oil Exploration in the Pre-Salt Layer
2021-2025 | Petrobras / UFMG
The project investigates the feasibility of AI-based models in three research lines: (i) seismic data inversion for rock characterization (SÍSMICA), (ii) automatic cycle identification through time-series analysis applied to stratigraphy (CICLOS), and (iii) their interplay. The VEQTOR group has focused on the CICLOS line, which has led to several journal and conference publications, as well as the development of a specialized tool called PetroCycle.
CNPq funds group members Gabriel Coutinho, Emanuel Juliano and Soffía Arnbjorg directly through specific research scholarships.
We also routinely receive funding from CNPq, CAPES and FAPEMIG for grad and undergrad scholarships through various institutional programs.
past projects
Industrial Applications of Quantum Computing
2023-2024 | CNPq / UFMG / LNCC / others
The project explores the practical potential of quantum computing at a transitional stage, where applications are already visible but current machines still suffer from high error rates. It connects theoretical researchers (in machine learning, optimization, graph theory, algorithms, and HPC) with Senai-Cimatec and Brazilian industry to develop quantum software solutions for computational demands that exceed the capabilities of traditional supercomputers.
Software Development Training 2021
2021-2022 | Samsung R&D Institute Brazil (SRBR) / UFMG
Training project for Samsung employees in algorithm techniques and implementation.
Machine Learning System for Predictive Maintenance
2019-2020 | Minasligas + Coss / UFMG
Development of a system to predict the need for maintenance in the motor of a bag filter, aiming to reduce the emission of solid particles into the atmosphere generated in the production of ferroalloys and metallic silicon through the use of electric furnaces.
Data Science Residency
2019 | Tenbu / UFMG
Training UFMG students to solve real-world problems presented by the partner company Tenbu.
Graphs, Matrices, and Quantum Computing
2019-2024 | FAPEMIG / UFMG
This project investigates the fundamental problem of determining the ideal configuration of particles in quantum walks to achieve desired outcomes, modeling the system as a graph whose dynamics are governed by the adjacency matrix. The proposal addresses inverse spectral problems, graph optimization, spectral algorithms, and semidefinite programming with applications to quantum algorithms for NP-hard problems and clustering, while also fostering collaborations, student training, and experimental exploration using tools from IBM and Microsoft.