The National Wallace Monument @ Stirling, Scotland (Credits: John Carroll)
You can check about my Lectureship in Big Data (Brazil) and my PhD in fundamental AI algorithms (Belgium) here.
You can find more information on how to explore the interactive map below here.
The affiliation information in the map above is updated sporadically.
You can check past news here.
You can check about nominations I received and the languages I speak here.
Financial details about the projects are provided in my CV.
You can check about my Graduate Apprenticeship (MSc) and Undergraduate dissertation and publication supervisions here.
Full author description for all my publications is provided in my CV. Manuscripts are publicly available here.
Can there be responsible AI without AI liability? Incentivizing generative AI safety through ex-post tort liability under the EU AI liability directive
This paper is the first contribution of my Lectureship in AI / Data Science in the UK, and discusses whether and how existing and novel regulation need to be revised to address generative AI (GenAI). The relevance of this paper is evidenced by its timing, as the paper was published at the peak of both the (i) surge in GenAI adoption and (ii) regulatory push from the European Union regarding AI. Importantly, this paper addresses policy and regulation, evidencing the multidisciplinary nature of my current Lectureship and research thereof.
A computational study on ant colony optimization for the traveling salesman problem with dynamic demands
This paper was the main contribution from the first Ph.D. thesis I co-supervised, and demonstrates how multi-objective and dynamic optimization intersect. The relevance of this paper is evidenced by its best paper award nomination at the EMO 2019 conference, where a preliminary version of the journal paper was first published. In addition, this paper is a concrete example of how I bridge different research topics into multi-disciplinary work.
Comparing community mobility reduction between first and second COVID-19 waves
This paper was the main contribution of my efforts in science publication and communication to assist in the fight against the COVID-19 pandemic. Indeed, the first author of this paper is one of the undergraduate students that I helped mobilize in those initiatives. The relevance of this paper is evidenced by the number of different continents and COVID-19 waves included in the assessment. In addition, this paper is a concrete example of how I use computational intelligence in the context of socially relevant problems.
Automatically designing state-of-the-art multi-and many-objective evolutionary algorithms
A large-scale experimental evaluation of high-performing multi-and many-objective evolutionary algorithms
Automatic component-wise design of multiobjective evolutionary algorithms
These papers comprise the contributions of my Ph.D. thesis, having been accepted for publication prior to my defense or shortly after. Their relevance is evidenced by their ongoing impact on the evolutionary computation community, one of the most important in the context of CI, and by the rigorous journals where they were published. More importantly, these papers demonstrate how I am able to plan and deliver on a research project. In detail, each paper meets an specific objective of my thesis proposal, incrementally achieving the general objective of the project.
Optimizing the logistics operations of distribution network operators from a multinational electric utility company
Retail sales forecasting for a Brazilian supermarket chain: an empirical assessment
Supermarket customer segmentation: a case study in a large Brazilian retail chain
These papers comprise the contributions of the data science projects and MSc+MPhil theses I (co-)supervised in partnership with private institutions. In detail, the first paper results from a collaboration with Neoenergia, the Brazilian subsidiary of the Spanish multinational utility company Iberdrola. In turn, the 2022 papers use AI techniques to model different business processes in the 3rd largest retail supermarket chain in the Northeast of Brazil, and are instrumental to assess the impact of the COVID-19 pandemic in the industry.
High school timetabling at a federal educational institute in Brazil
Time-series features for predictive policing
Towards a crime hotspot detection framework for patrol planning
These papers comprise the contributions of the data science projects and MSc+MPhil theses I (co-)supervised in partnership with public institutions. The relevance of these papers is evidenced by the socially relevant scenarios they address. In detail, the first paper focuses on the Brazilian Federal Network of Vocational, Scientific and Technological Education, which provides education to over two million students, with over half of the students that declared income, gender, and ethnicity coming from low income families, being women, and self-declaring as non-white. In turn, the 2018 papers address predictive policing to assist the local government in the forecasting of criminal occurrences.
Evaluating anytime performance on NAS-Bench-101
iSklearn: automated machine learning with irace
Comparing contextual embeddings for semantic textual similarity in Portuguese
These papers are the contributions of MSc+MPhil theses I supervised in deep and automated machine learning. The relevance of these papers is evidenced by the state-of-the-art techniques that were employed. In addition, the application domains considered are among the most relevant that use unstructured data, namely computer vision, natural language processing, and time series forecasting. Importantly, these papers demonstrate that I understand the technological complexity of current state-of-the-art AI models, their potential impact on society, and therefore their need for accountability.
Revisiting Pareto-optimal multi-and many-objective reference fronts for continuous optimization
Archiver effects on the performance of state-of-the-art multi-and many-objective evolutionary algorithms
An empirical assessment of the properties of inverted generational distance on multi-and many-objective optimization
These papers comprise follow-up works on my Ph.D. thesis. The relevance of these papers is evidenced by their ongoing impact on the evolutionary computation community, as well as the conferences where they were published, which are among the top-tier venues in their field. More importantly, these papers are a concrete example that the work I conducted in my Ph.D. was seminal to relevant future work. In addition, they demonstrate that I understand that seeking autonomy as an independent researcher does not mean discontinuing previous research.
You can check about my COVID-19 engagement and my communication and networking activities in Brazil here.
Empowering decision-subjects & end-users to audit AI applications
AI Data Ready: Challenges and opportunities for companies preparing for AI
Supporting society to assess AI
FAIRTECH by design: assessing and addressing the social impacts of artificial intelligence
Promoting and sustaining accountability in artificial intelligence applications
