Mateus de Oliveira Oliveira


Presentation

    • I’m a Senior Lecturer at Stockholm University’s Department of Computer and System Sciences (Sweden).
     
     
    •  I’m currently leading two research projects. SYMBOALGO  is a 12 Million NOK project in the field of symbolic algorithms. AUTOPROVING is a 8 Million NOK project in the field of automated reasoning.
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    •  My main research interest is the application of techniques from computational logic, computational complexity theory and structural graph theory in the study of problems relevant to Artificial Intelligence and related areas.

Contact

  • oliveira@dsv.su.se

Grants

  • 2021-2025 – SYMBOALGO – Symbolic Algorithms: A Parameterized Approach. Research Council of Norway, FRIPRO, Ground-Breaking Research program (12 Million NOK). 
  • 2019-2023 – AUTOPROVING – Automated Theorem Proving from the Mindset of Parameterized Complexity Theory. Research Council of Norway, IKTPLUSS, Young Researchers Talent Grant (8 Million NOK).
  • 2020-2021 – Algorithmic Automata Theory: A Multivariate Approach. DAAD/RNC Mobility Program. The goal of this grant is to fund short-term visits of PhD students from the University of Bergen to the University of Trier (Germany). (100 Thousand NOK).
  • 2020-2021 – SPIRE Grant – The goal of this grant is to fund short term visits of international researchers to the University of Bergen. (63 Thousand NOK)
  • 2019-2019 – University of Bergen, Positioning Grant (50 Thousand NOK). The goal of this grant was to build international Collaboration.

Research Team

  • Boris Djalal – Researcher (2022-Present) – University of Bergen. Boris working in my project SYMBOALGO. Boris is working with proof formalization. 

  • Wim van den Broeck – Ph.D. Student (2022-Present) – University of Bergen. Wim is working in my project SYMBOALGO. I’m Wim’s main supervisor.

  • Farhad Vadiee – Ph.D. Student (2019-Present)- University of Bergen. Farhad is working in my project AUTOPROVING. I’m Farhad main supervisor.

  • Magnus Hegdahl – Bachelor Student (2022-Present) – University of Bergen. Magnus is working as a research assistant in my project AUTOPROVING.

Past Students and Team Members

  • Emmanuel Arrighi – Ph.D. Student (2019-2022) – University of Bergen. I was Emmanuel’s main supervisor. Emmanuel successfully defended his thesis on 25/May/2022. 

Participation in Program Committees

IJCAI 2023 (Senior PC member), SEA 2023 (PC member), AAAI 2023 (PC member),  IJCAI 2022 (PC member), IWOCA 2022 (PC member), LSFA 2022 (PC member), AAAI 2021 (PC member)

Preprints

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Publications

2023

  • Order Reconfiguration under Width Constraints
    Emmanuel Arrighi, Henning Fernau, Mateus de Oliveira Oliveira, Petra Wolf
    Journal of Graph Algorithms and Applications (Accepted)

  • From Width-Based Model Checking to Width-Based Automated Theorem Proving
    Mateus de Oliveira Oliveira and Farhad Vadiee
    37th AAAI Conference on Artificial Intelligence (AAAI 2023). Accepted. 
  • Synchronization and Diversity of Solutions 
    Emmanuel Arrighi, Henning Fernau, Mateus de Oliveira Oliveira and Petra Wolf
    37th AAAI Conference on Artificial Intelligence (AAAI 2023). Accepted.

 2022

  • Synthesis and Analysis of Petri Nets from Causal Specifications. 
    Mateus de Oliveira Oliveira.
    34th International Conference on Computer Aided Verification (Accepted)
  • Mortality and Edge-to-Edge Reachability are Decidable on  Surfaces
    Mateus de Oliveira Oliveira and Olga Tveretina
    ACM International Conference on Hybrid Systems (HSCC 2022). Accepted.
  • On the Satisfiability of Smooth Grid CSPs.
    Vasily Alferov and Mateus de Oliveira Oliveira
    20th Symposium on Experimental Algorithms (SEA 2022). Accepted.
  • Learning from Positive and Negative Examples: Dichotomies and Parameterized Algorithms
    Jonas Ling, Mateus  de Oliveira Oliveira and Petra Wolf
    33rd International Workshop on Combinatorial Algorithms (IWOCA 2022). Accepted. 

 2021

  • Succinct Certification of Monotone Circuits.
    Mateus Rodrigues Alves, Mateus de Oliveira Oliveira, Janio Carlos Nascimento Silva and Uéverton dos Santos Souza.
    Theoretical Computer Science. (Accepted) 
    obs: conference version appeared at COCOON 2020
  • On the Complexity of  Intersection Non-emptiness for Star-Free Language Classes. 
    Emmanuel Arrighi, Henning Fernau, Stefan Hoffmann, Markus Holzer, Ismael Jecker, Mateus De Oliveira Oliveira and Petra Wolf
    41st Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2021)
  • Unitary Branching Programs: Learnability and Lower Bounds
    Fidel Andino, Maria Kokkou, Mateus de Oliveira Oliveira, Farhad Vadiee
    38th International Conference on Machine Learning (ICML 2021)
  • Order Reconfiguration under Width Constraints
    Emmanuel Arrighi, Henning Fernau, Mateus de Oliveira Oliveira, Petra Wolf
    46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021)
  • Co-degeneracy and co-treewidth: Using the complement to solve dense instances
    Gabriel Duarte, Mateus De Oliveira Oliveira and Uéverton Souza
    46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021)

2020

  • Second-Order Finite Automata
    Alexsander Andrade de Melo, Mateus de Oliveira Oliveira
    15th International Computer Science Symposium in Russia (CSR 2020) (Invited Paper )

2019

2018

2017

  • Parameterized Provability in Equational Logic
    Mateus de Oliveira Oliveira
    Proc. of the 26th International Conference on Automated Reasoning with Analytic Tableaux and Related Methods (TABLEAUX 2017).
    Brasília, Brazil, September 2017

2016

2015

Earlier

Automated Theorem Proving from the Mindset of Parameterized Complexity Theory

The idea of proving or disproving mathematical statements using automated procedures has been contemplated for at least one century. Nevertheless, even though the field of automated reasoning has reached important milestones during the past few decades, the question of whether computers can significantly speed up the process of proof construction remains elusive.

The goal of this project is to identify a series of numerical parameters that are typically small in humanly produced proofs. Intuitively these parameters are intended to provide a numerical quantification of the complexity of a proof. Using information about these parameters, we will develop new algorithms that will be able to either find a proof of a given predetermined complexity or to determine that no such proof exists.

As a byproduct, we expect that our results will have the potential to improve significantly the automation capabilities of a variety of tools, such as proof assistants, software verification tools, specialist systems, etc.

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