I have joined the University of Stirling in 2023 as a Lecturer in A.I./Data science. Previously, I worked at UFRN (Brazil) from 2017 to 2023 as an Assistant Professor. My Ph.D. degree in Sciences de L'Ingénieur et Technologie was obtained at Université Libre de Bruxelles (Belgium) in 2016.
My thesis on computational intelligence (CI) was seminal to my current research on data science (DS), artificial intelligence (AI), and their impact on socially relevant problems. Regarding DS, I propose and collaborate with applied projects with both the public and private sectors. Partners include the Brazilian Judicial Branch and Ministry of Education, as well as regional and (multi-)national companies in fields as diverse as retail, telecommunications, and energy. Concerning AI, I supervise graduate students on theses involving deep and automated machine learning, as well as the intersection of multi-objective optimization with other CI domains, such as multi-dimensional visualization and dynamic optimization. Most importantly, I have a deep concern for socially relevant problems, having for instance assisted in the fight against the COVID-19 pandemic through science publication and communication, in an attempt to counter the intensive disinformation campaign held in Brazil.
I am currently applying for fellowships from the United Kingdom Research and Innovation (UKRI), with the help of senior colleagues from other UK universities. The goal of the project is to propose an end-to-end policy framework to be used by governments and AI developers alike to ensure that AI applications be devised and operated in an accountable way. In the initial part of this project, we will survey current and future relevant real-world examples, in addition to disinformation through social media, where the lack of appropriate AI regulation (potentially) incurs significant social damage. Next, our aim will be to survey the existing legal, economical, and technological imitations for an end-to-end accountable AI policy framework. At this stage, we will be able to propose a framework that overcomes those limitations, which we will evaluate using the relevant real-world examples previously identified. The contributions of this project are timely and will have a significant impact on society. Namely, the surveys envisioned should become central in the literature of AI accountability. In addition, the framework we will propose and its evaluation on real-world examples will be instrumental in the ongoing worldwide discussions on the regulation of AI applications. To maximize the impact of these contributions, we will create the Potentially Incurred Social Damage from Artificial Intelligence Observatory (PISD.ai), through which all project deliverables will be made publicly available and society feedback will be received.
Book Chapter
Automatic Configuration of Multi-objective Optimizers and Multi-objective Configuration
Bezerra LCT, López-Ibáñez M & Stützle T (2020) Automatic Configuration of Multi-objective Optimizers and Multi-objective Configuration. In: High-Performance Simulation-Based Optimization. Studies in Computational Intelligence. Springer International Publishing, pp. 69-92. https://doi.org/10.1007/978-3-030-18764-4_4
Article
Automatically Designing State-of-the-Art Multi- and Many-Objective Evolutionary Algorithms
Bezerra LCT, López-Ibáñez M & Stützle T (2020) Automatically Designing State-of-the-Art Multi- and Many-Objective Evolutionary Algorithms. Evolutionary Computation, 28 (2), pp. 195-226. https://doi.org/10.1162/evco_a_00263
Conference Paper (published)
Bezerra LCT, López-Ibáñez M & Stützle T (2019) Archiver effects on the performance of state-of-the-art multi- and many-objective evolutionary algorithms. In: GECCO '19: Genetic and Evolutionary Computation Conference, Prague Czech Republic, 13.07.2019-17.07.2019. ACM, pp. 620-628. https://doi.org/10.1145/3321707.3321789
Article
Bezerra LCT, López-Ibáñez M & Stützle T (2018) A Large-Scale Experimental Evaluation of High-Performing Multi- and Many-Objective Evolutionary Algorithms. Evolutionary Computation, 26 (4), pp. 621-656. https://doi.org/10.1162/evco_a_00217
Conference Paper (published)
Bezerra LCT, López-Ibáñez M & Stützle T (2017) An Empirical Assessment of the Properties of Inverted Generational Distance on Multi- and Many-Objective Optimization. In: Evolutionary Multi-Criterion Optimization, volume 10173. Lecture Notes in Computer Science. Evolutionary Multi-Criterion Optimization (EMO 2017), Münster, Germany, 19.03.2017-22.03.2017. Springer International Publishing, pp. 31-45. https://doi.org/10.1007/978-3-319-54157-0_3
Article
Automatic Component-Wise Design of Multiobjective Evolutionary Algorithms
Bezerra LCT, Lopez-Ibanez M & Stutzle T (2016) Automatic Component-Wise Design of Multiobjective Evolutionary Algorithms. IEEE Transactions on Evolutionary Computation, 20 (3), pp. 403-417. https://doi.org/10.1109/tevc.2015.2474158
Conference Paper (published)
Bezerra LCT, López-Ibáñez M & Stützle T (2015) To DE or Not to DE? Multi-objective Differential Evolution Revisited from a Component-Wise Perspective. In: Evolutionary Multi-Criterion Optimization, volume 9018. Lecture Notes in Computer Science. Evolutionary Multi-Criterion Optimization (EMO 2015), Guimaraes, Portugal, 29.03.2015-01.04.2015. Springer International Publishing, pp. 48-63. https://doi.org/10.1007/978-3-319-15934-8_4
Conference Paper (published)
Bezerra LCT, López-Ibáñez M & Stützle T (2015) Comparing Decomposition-Based and Automatically Component-Wise Designed Multi-Objective Evolutionary Algorithms. In: Evolutionary Multi-Criterion Optimization, volume 9018. Lecture Notes in Computer Science. Evolutionary Multi-Criterion Optimization (EMO 2015), Guimaraes, Portugal, 29.03.2015-01.04.2015. Springer International Publishing, pp. 396-410. https://doi.org/10.1007/978-3-319-15934-8_27
Conference Paper (published)
Bezerra LCT, López-Ibáñez M & Stützle T (2014) Deconstructing Multi-objective Evolutionary Algorithms: An Iterative Analysis on the Permutation Flow-Shop Problem. In: Learning and Intelligent Optimization, volume 8426. Lecture Notes in Computer Science. Learning and Intelligent Optimization (LION 2014), Gainesville, FL, USA, 16.02.2014-21.02.2014. Springer International Publishing, pp. 157-172. https://doi.org/10.1007/978-3-319-09584-4_16
Conference Paper (published)
Automatic Design of Evolutionary Algorithms for Multi-Objective Combinatorial Optimization
Bezerra LCT, López-Ibáñez M & Stützle T (2014) Automatic Design of Evolutionary Algorithms for Multi-Objective Combinatorial Optimization. In: Parallel Problem Solving from Nature, volume 8672. Lecture Notes in Computer Science. Parallel Problem Solving from Nature (PPSN 2014), Ljubljana, Slovenia, 13.09.2014-17.09.2014. Springer International Publishing, pp. 508-517. https://doi.org/10.1007/978-3-319-10762-2_50
Conference Paper (published)
An Analysis of Local Search for the Bi-objective Bidimensional Knapsack Problem
Bezerra LCT, López-Ibáñez M & Stützle T (2013) An Analysis of Local Search for the Bi-objective Bidimensional Knapsack Problem. In: Evolutionary Computation in Combinatorial Optimization, volume 7832. Lecture Notes in Computer Science. Evolutionary Computation in Combinatorial Optimization (EvoCOP 2013), Vienna, Austria, 03.04.2013-05.04.2013. Springer Berlin Heidelberg, pp. 85-96. https://doi.org/10.1007/978-3-642-37198-1_8
Conference Paper (published)
Automatic Generation of Multi-objective ACO Algorithms for the Bi-objective Knapsack
Bezerra LCT, López-Ibáñez M & Stützle T (2012) Automatic Generation of Multi-objective ACO Algorithms for the Bi-objective Knapsack. In: Swarm Intelligence, volume 7461. Lecture Notes in Computer Science. Swarm Intelligence (ANTS 2012), Brussels, Belgium, 12.09.2012-14.09.2012. Springer Berlin Heidelberg, pp. 37-48. https://doi.org/10.1007/978-3-642-32650-9_4
My previous position at Federal University of Rio Grande do Norte (UFRN) as a Lecturer in Big Data has provided me with the opportunity to help (re)formulate different educational programmes undergraduate and postgraduate) and supervise talented undergraduate, postgraduate apprenticeship, and Master’s students. I have also successfully co-supervised a PhD student, since I was not allowed to be a main PhD supervisor yet. Importantly, I have helped propose artificial intelligence (AI) and data science (DS) tracks for both the undergraduate and Master’s programmes, as well as a novel professional doctorate programme in information technology (IT). Finally, I have taken a proactive approach to learning, having designed and delivered 19 different course modules, which can be broadly categorized into computational thinking (ranging from abstract data types to coding interview preparation) and AI/DS (with a focus on non-programmers). All of these course modules were designed with an emphasis on self-taught learning, which made them ideal for the COVID-19 pandemic period (and online learning thereof). In addition to having published a book chapter about the methodology I have employed, I have also partnered with Huawei Telecommunications in Brazil to provide an HCIA-AI deep learning certificate online training.
