Leandro De Castro

Leandro De Castro
University of Campinas | UNICAMP · Faculty of Technology

B.Sc (El. Eng.); M.Sc. (El. Eng.); Ph.D. (Comp. Eng.); Post-Doc (Computing); MBA (Strategic Management)

About

299
Publications
84,444
Reads
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13,935
Citations
Citations since 2017
45 Research Items
2996 Citations
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20172018201920202021202220230100200300400500
Introduction
I was a Research Associate at the University of Kent at Canterbury (2001-2002), a Visiting Professor at the Malaysian Technological University (2005), a Visiting Professor at Unicamp (2012), and a Visiting Researcher at the University of Salamanca (2014). I was also a Research Professor at the Masters Program in Informatics at Unisantos (2003-2007), and an Adjunct Professor at Mackenzie (2008-2022). My research focuses on Artificial Intelligence, Machine Learning and Natural Computing.
Additional affiliations
February 2008 - June 2022
Universidade Presbiteriana Mackenzie
Position
  • Managing Director
March 2003 - December 2008
Catholic University of Santos
Position
  • Research Professor
Education
February 2007 - December 2007
Catholic University of Santos
Field of study
  • Business Administration
October 1998 - May 2001
University of Campinas
Field of study
  • Computer Engineering
March 1997 - October 1998
University of Campinas
Field of study
  • Computer Engineering

Publications

Publications (299)
Chapter
A proper analysis and interpretation of resting-state function Magnetic Resonance Imaging (rs-fMRI) signals is highly dependent upon the capability of discriminating signal from noise. From among the many non-system-related types of noise, the physiological noise and noise related to motion are the most relevant ones. This paper introduces two scor...
Article
Remote Laboratories (RLs) are software and hardware tools that allow students to remotely perform real experiments by means of an online system or platform. They represent an evolution in the learning process by making the execution of real-world experiments accessible for many students at distance. Learning Analytics (LAs), by contrast, is the res...
Chapter
Full-text available
Assuming nature can be investigated and understood as an information processing system, this chapter aims to explore this hypothesis in the field of ecosystems. Therefore, based on the concepts of biogeography, it further investigates a computational approach called biogeographic computation to the study of ecosystems. The original proposal in the...
Book
Full-text available
Computational social science is regarded as a research method that provides an unprecedented breadth and depth of data to classify and analyze how human interaction occurs and provide a different dimension to studies of collective human behavior. Computational social science refers to computational methods and approaches to study the social science...
Chapter
Full-text available
Each person projects behavioral patterns through actions. Even in a virtual environment we express our way of seeing, feeling, and reacting to the world. The analysis of the data generated allows the identification of pattern behaviors associated with users. Therefore, it is possible to obtain a better understanding of the user, the image he/she de...
Article
Full-text available
Objective of the study: To propose and evaluate the DIMEP methodology for diagnosing and monitoring the maturity of startups in academic institutions, based on dimensions, subdimensions and maturity levels for evaluating startups at different entrepreneurial journey stages. Methodology: Exploratory, with the proposal of DIMEP, based on the concepts...
Book
Full-text available
This book had a main motivation for its conception, which is the need to disseminate science, particularly natural computing. Its primary objective is to spread natural computing to those who do not know it or who have little access to this subject field, but who want to know a little more about what is being investi-gated by researchers and which...
Article
Full-text available
Recommender Systems (RS) are a subclass of information filtering systems that seek to predict the rating or preference a user would give to an item. e-Recruitment is one of the domains in which RS can contribute due to presenting a list of interesting jobs to a candidate or a list of candidates to a recruiter. This study presents an up-to-date syst...
Conference Paper
Full-text available
This paper proposes a method for asset allocation based on partitional clustering. This method is different from the approaches already proposed in the literature, which essentially use either an optimization-based approach or a hierarchical clustering algorithm to allocate resources in assets. After finding the clusters, the method uniformly alloc...
Chapter
Recommender systems aim to effectively recommend items to the user based on their profile. An online recruitment system recommends jobs for a candidate according to his profile and can also act in reverse, recommending more qualified candidates for a particular job. Defining which variables will be used impacts directly the recommendation quality s...
Chapter
e-Recruitment Recommender Systems have been attracting attention over the last few years. It is an economically relevant field and can potentially revolutionize how organizations execute talent search and acquisition. This paper briefly discusses the e-Recruitment problem and presents a framework together with three recommendation models aiming to...
Article
Full-text available
Over the past years, many approaches to perform asset allocation have been proposed in the literature. Most of them tackle this problem as an optimization task, where the goal is to maximize return, whilst minimizing the risk. However, such approaches require the inversion of a positive-definite covariance matrix, usually resulting in the concentra...
Article
Over the last decades, the number of Swarm Intelligence algorithms proposed in the literature has increased considerably. However, most algorithms do not follow an adequate scientific rigour neither the principles of Swarm Intelligence, reproducing similar computational procedures of many other approaches, but by means of a different metaphor. In t...
Chapter
Full-text available
Word2Vec has become one of the most relevant neural networks to generate word embeddings for NLP applications. Despite that, little has been investigated in terms of its sensitivity to the word vectors’ length (n) and the window size (w). Thus, the present paper performs a sensitivity analysis of Word2Vec when applied to generate word embeddings fo...
Chapter
Full-text available
The automatic detection of topics in a set of documents is one of the most challenging and useful tasks in Natural Language Processing. Word2Vec has proven to be an effective tool for the distributed representation of words (word embeddings) usually applied to find their linguistic context. This paper proposes the use of a Self-Organizing Map (SOM)...
Conference Paper
Full-text available
On the one hand, Deep Neural Networks have emerged as a powerful tool for solving complex problems in image and text analysis. On the other, they are sophisticated learning machines that require deep programming and math skills to be understood and implemented. Therefore, most researchers employ toolboxes and frameworks to design and implement such...
Article
Full-text available
The literature is now filled with swarm intelligence algorithms developed by taking inspiration from a number of insects and other animals and phenomena, such as ants, termites, bees, fishes and cockroaches, to name just a few. Many, if not most, of these bioinspirations carry with them some common issues and features which happen at the individual...
Article
Chord progressions play an important role in Western tonal music. For a novice composer, the creation of chord progressions can be challenging because it involves many subjective factors, such as the musical context, personal preference and aesthetic choices. This work proposes ChordAIS, an interactive system that assists the user in generating cho...
Presentation
Full-text available
Essa apresentação foi feita na ERAD/RS 2019. Esta apresenta é uma visão geral do paralelismo de tarefas utilizando a especificação OpenMP 4.5. Além de apresentar esses conceitos, eles serão aplicados em algoritmos de computação natural para resolver problemas de agrupamento e otimização.
Article
Full-text available
This paper presents the basic concepts of task parallelism using OpenMP 4.5. Besides those concepts, it also describes its usage in natural computing to solve clustering and optimization problems.
Article
Full-text available
Temperament and Psychological Types can be defined as innate psychological characteristics associated with how we relate with the world, and often influence our study and career choices. Furthermore, understanding these features help us manage conflicts, develop leadership, improve teaching and many other skills. Assigning temperament and psycholog...
Chapter
Temperament is a set of innate tendencies of the mind related with the processes of perception, analysis and decision making. The purpose of this paper is to predict Twitter users temperament based on Portuguese tweets and following Keirsey’s model, which classifies the temperament into artisan, guardian, idealist and rational. The proposed methodo...
Article
Full-text available
The present work explores bacterial colonies and their individual and social behaviours under the lens of complex adaptive systems. We initially provide a background on the biology of bacteria to describe important phenomena, such as quorum-sensing, individual and collective behaviours, adaptation, evolution and self-organization over the influence...
Article
Full-text available
Bacterial colonies perform a cooperative and distributed exploration of the environmental resources by using their quorum-sensing mechanisms. This paper describes how bacterial colony networks and their skills to explore resources can be used as tools for mining association rules in static and stream data. A new algorithm is designed to maintain di...
Article
Full-text available
Understanding how careers evolve is very important for us, so we can make better professional decisions; for companies, so they can better plan their internal organization career progressions; and also for the governments, so they can better plan their labor market and economic policies. In this paper we model career progression as a graph, called...
Conference Paper
Data generation has grown rapidly over the recent years. Different types of products and services are offered daily on the Internet. Finding out elegant, flexible and robust strategies to deal with this amount of data in a static way is one goal of data mining, whilst the data stream mining works in dynamic environments. The searching of co-occurre...
Data
I'd like to thank my friend Bela Roque who present my paper in Conference Distributed Computing and Artificial Intelligence (DCAI 2018). Toledo (Spain) | 20th-22nd June, 2018.
Chapter
Full-text available
Many people use social media nowadays to express their emotions or opin-ions about something. This paper proposes the use of a deep learning net-work architecture for emotion classification in Twitter messages, using the six emotions model of Ekman: happiness, sadness, anger, fear, disgust and surprise. We collected the tweets from a labeled datase...
Chapter
Bacterial colonies perform a cooperative and distributed exploration of the environmental resources. This paper describes how bacterial colony networks and their skills to search resources can be used as tools for mining association rules in static and stream data. The proposed algorithm is designed to maintain diverse solutions to the problems at...
Chapter
Full-text available
Assuming nature can be investigated and understood as an information processing system, this chapter aims to explore this hypothesis in the field of ecosystems. Therefore, based on the concepts of biogeography, it further investigates a computational approach called biogeographic computation to the study of ecosystems. The original proposal in the...
Technical Report
Full-text available
Os veículos aéreos não tripulados (UAVS – do inglês, Unmanned Aerial Vehicles) possibilitam uma série de aplicações, o que representa uma grande motivação para a realização de pesquisas que buscam a navegação autônoma em diferentes cenários. As aplicações de UAVs autônomos são as mais diversas e incluem a detecção de alvos, escolta de objetos e alv...
Article
Full-text available
Combinatorial optimization problems are broadly studied in the literature. On the one hand, their challenging characteristics, such as the constraints and number of potential solutions, inspires their use to test new solution techniques. On the other hand, the practical application of these problems provides support of daily tasks of people and com...
Article
Full-text available
Vehicle routing problems constitute a class of combinatorial optimization tasks that search for optimal routes (e.g., minimal cost routes) for one or more vehicles to attend a set of nodes (e.g., cities or customers). Finding the optimal solution to vehicle routing tasks is an NP-hard problem, meaning that the size of problems that can be solved by...
Article
Full-text available
Multiobjective clustering techniques have been used to simultaneously consider several complementary aspects of clustering quality. They optimize two or more cluster validity indices simultaneously, they lead to high-quality results, and have emerged as attractive and robust alternatives for solving clustering problems. This paper provides a brief...
Article
A clustering ensemble combines in a consensus function the partitions generated by a set of independent base clusterers. In this study both the employment of particle swarm clustering (PSC) and ensemble pruning (i.e., selective reduction of base partitions) using evolutionary techniques in the design of the consensus function is investigated. In th...
Conference Paper
Temperament is an innate psychological characteristic associated with how we relate with the world. This feature is often used to direct careers, manage conflicts, develop leadership, improve teaching, etc. The data generated by social media users represent user behavior facing the various situations of everyday life. With this, machine learning te...
Conference Paper
The Traveling Salesman Problem (TSP) is a combinatorial optimization problem widely used to test new heuristics. Bee-inspired algorithms are receiving great attention from the Swarm Intelligence field due to their capability of providing good solutions in reasonable time to complex problems. This paper takes the optBees, a bee-inspired algorithm us...
Chapter
Full-text available
With the growth of social media in recent years, there has been an increasing interest in the automatic characterization of users based on the informal content they generate. In this context, the labeling of users in demographic categories, such as age, ethnicity, origin and race, among the investigation of other attributes inherent to users, such...
Conference Paper
The Traveling Salesman Problem (TSP) is extensively used to test new algorithms that tackle combinatorial optimiza-tion problems. Bee inspired algorithms are receiving a con-siderable attention from the Swarm Intelligence field. This paper presents the TSPoptBees, a bee inspired algorithm to solve the TSP. A vast discussion is made in regards to th...
Conference Paper
Multiobjective clustering techniques have been used to simultaneously consider several complementary aspects of clustering quality. They optimize more than one cluster validity index simultaneously, leading to high-quality re-sults, and have emerged as attractive and robust alternatives for clustering problems. This paper proposes a bee-inspired mu...
Article
Full-text available
Over the past two decades a wide range of nature-inspired clustering algorithms has been proposed in the literature with competitive performance when applied to solving real-world complex problems. One common feature of most of these algorithms is the need to set a number of internal parameters so that they can be suitably applied to these problems...
Conference Paper
Full-text available
Bacterial colonies perform a cooperative distributed exploration of the environment. This paper describes bacterial colony networks and their skills to explore resources as a tool for mining association rules in databases. The proposed algorithm is designed to maintain diverse solutions to the problem at hand, and its performance is compared to oth...
Conference Paper
Bacterial colonies perform a cooperative distributed exploration of the environment. This paper describes bacterial colony networks and their skills to explore resources as a tool for mining association rules in databases. The proposed algorithm is designed to maintain diverse solutions to the problem at hand, and its performance is compared to oth...
Conference Paper
This paper proposes a modification in the Fuzzy Particle Swarm Clustering (FPSC) algorithm such that membership degrees are used to weight the step size in the direction of the local and global best particles, and in its movement in the direction of the input data at every iteration. This results in the so-called Membership Weighted Fuzzy Particle...
Conference Paper
This paper presents a new thresholding methodology for complex background images with an application to the courtesy amount of Brazilian bank checks. Courtesy amount images present a complex background and the proposal of an automatic thresholding process brings benefits to other steps in bank check clearance, such as the Optical Character Recognit...
Article
Data clustering aims to segment a database into groups of objects based on the similarity among these objects. Due to its unsupervised nature, the search for a good-quality solution can become a complex process. There is currently a wide range of clustering algorithms, and selecting the best one for a given problem can be a slow and costly process....
Conference Paper
Full-text available
Chord progressions are widely used in music. The automatic generation of chord progressions can be challenging because it depends on many factors, such as the musical context, personal preference, and aesthetic choices. In this work, we propose a penalty function that encodes musical rules to automatically generate chord progressions. Then we use a...
Article
Full-text available
Bladder cancer occurs in the epithelial lining of the urinary bladder and is amongst the most common types of cancer in humans, killing thousands of people a year. This paper is based on the hypothesis that the use of clinical and histopathological data together with information about the concentration of various molecular markers in patients is us...
Conference Paper
Full-text available
This work uses data collected by honeypots to create rules and signatures for intrusion detec-tion systems. The rules are extracted from deci-sion trees constructed based on the data of a real honeypot installed on an internet connection without any filter. The results of the experiments showed that the extraction of rules for an intru-sion detecti...
Conference Paper
Clustering is one of the most important tasks in data mining and can be defined as the process of partitioning objects into groups or clusters, such that objects in the same group are more similar to one another than to objects be¬longing to oth-er groups. Many algorithms to solve data clustering prob-lems have been presented in the literature. Rec...
Article
Social media allow web users to create and share content pertaining to different subjects, exposing their activities, opinions, feelings and thoughts. In this context, online social media has attracted the interest of data scientists seeking to understand behaviours and trends, whilst collecting statistics for social sites. One potential applicatio...
Conference Paper
Full-text available
This paper reports how OptBees, an algorithm inspired by the collective decision-making of bee colonies, per- formed in the test bed developed for the Special Session & Competition on Real-Parameter Single Objective Optimization at CEC-2014. The test bed includes 30 scalable functions, many of which are both non-separable and highly multi-modal. Re...
Article
Twitter is a microblog service that generates a huge amount of textual content daily. All this content needs to be explored by means of text mining, natural language processing, information retrieval, and other techniques. In this context, automatic keyword extraction is a task of great usefulness. A fundamental step in text mining techniques consi...
Conference Paper
Different methods have been used to train radial basis function neural networks. This paper proposes a bee-inspired algorithm to automatically select the number and location of basis functions to be used in such RBF network. The algorithm was designed to solve data clustering problems, where the centroids of clusters are used as centers for the RBF...
Article
Full-text available
Ecology plays a central role in biology and deserves special attention in scientific education. Nonetheless, the teaching and learning of ecology face a number of difficulties. In order to tackle these difficulties, electronic games have recently been used to mediate ecology learning. This paper presents an electronic game that fulfills these gaps...
Article
Twitter is a microblog service that generates a huge amount of textual content daily. All this content needs to be explored by means of text mining, natural language processing, information retrieval, and other techniques. In this context, automatic keyword extraction is a task of great usefulness. A fundamental step in text mining techniques consi...
Conference Paper
Full-text available
Based on the concept that the structure of nature is informational and the dynamics (changes of state) is computational, we analyze the mechanisms of interaction and decision making that are present in natural systems as information and computation respectively.
Conference Paper
Full-text available
Social media allow web surfers to produce and share content about different subjects, exposing their activities, opinions, feelings and thoughts. In this context, online social media has attracted the interest of data analysis researchers seeking to infer behaviors and trends, besides creating statis-tics involving social sites. A possible research...
Conference Paper
Full-text available
Electronic commerce (e-commerce) has grown rapidly over the past years. Products, services and information of different types are offered daily for many Internet users. Finding out an appropriate strategy to offer a product to each customer in a personalized fashion is the goal of a recommend-er system. This association between items is a task that...
Conference Paper
Full-text available
The amount of data generated in different knowledge areas has made necessary the use of data mining tools capable of automatically analyzing and extracting knowledge from datasets. Clustering is one of the most important tasks in data mining and can be defined as the process of partitioning ob-jects into groups or clusters, such that objects in the...
Conference Paper
Full-text available
Finding a good clustering solution for an unknown problem is a challenging task. Evolutionary algorithms have proved to be reliable methods to search for high quality solutions to complex problems. The present paper proposes a new set of genetic operators for the Fast Evolutionary Algorithm for Clustering (Fast-EAC) to improve the solution quality...