1.. Research Assistant as Master’s Candidate

• Department of Computer Science of the Faculty of Sciences of University of Porto
• Porto, Portugal
• September 2023 - July 2024

Short Description:

• Conducted independent research under the mentorship of Prof. Pedro Manuel Pinto Ribeiro and Prof. Miguel Eduardo Pinto da Silva, with a focus on advancing Graph Neural Networks (GNNs) for motif discovery.
• Explored the foundational principles, limitations, and current methodologies of GNNs, critically analyzing state-of-the-art techniques and identifying significant gaps in the literature.
• Designed and executed both theoretical and empirical experiments addressing these gaps, culminating in an alternative to motif estimation using GNNs.
• Led the drafting of a manuscript detailing these findings for publication.

2.. Research Assistant

• INESC TEC - Artificial Intelligence and Decision Support Research Center
• Porto, Portugal
• February 2022 - January 2023

Short Description:

• Collaboration between Carnegie Mellon (CMU), INESC TEC/ID, NOVA.ID.FCT and FCiências.ID to deanonymize Dark Web Traffic of Mix Networks for Cybercrime Investigation (project: DAnon)
• Applied machine learning methods, including reinforcement learning and genetic algorithms, to extract origin relay information from encrypted TCP connections.
• Developed and implemented heuristic-based algorithms for temporal sequence similarity measurement to enhance relay matching accuracy.
• Researched the applicability of the described methods to demultiplex encrypted TCP requests from a single logical connection.
• Authored a comprehensive technical report documenting methodologies, findings, and implications for secure communications analysis (not publicly available).

3.. Research Assistant

• INESC TEC - HumanISE Research Center
• Porto, Portugal
• February 2021 - September 2021

Short Description:

• Collaborated with a research team (MoST project) to design advanced spatio-temporal data structures, integrating rigorous time and space complexity analysis to establish defined performance boundaries, beating the state-of-the-art.
• Explored structural applications to challenging spatio-temporal problems, notably the “Teapot in a Stadium” problem, deriving critical insights that contributed to error correction and refinement of the models.
• Led the drafting of a manuscript detailing these findings for publication.

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