Rafael Ris-Ala José Jardim

Rafael Ris-Ala José Jardim
University of São Paulo | USP · Luiz de Queiroz College of Agriculture (ESALQ)

Doctor of Philosophy student
Data Scientist

About

22
Publications
2,301
Reads
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196
Citations
Introduction
Rafael Ris-Ala is a Professor of Research Methodology at the Luiz de Queiroz College of Agriculture (ESALQ) at the University of São Paulo (USP), an Assistant Professor I of Machine Learning at the Pontifical Catholic University of Minas Gerais (PUC Minas), and a Professor of Machine Learning and Research Methodology at the XP Education College (XPe). He has supervised several professionals, conducted more than 80 academic projects and evaluated more than 140 projects.
Additional affiliations
March 2023 - present
Pontifical Catholic University of Minas Gerais
Position
  • Professor
Description
  • Professor of Artificial Intelligence and Machine Learning Professor of Reinforcement Learning
August 2019 - January 2022
Federal University of Rio de Janeiro
Position
  • Professor
Description
  • Professor of Management Project
May 2021 - present
Faculdade XP Educação (XPE)
Position
  • Professor
Description
  • Professor of Machine Learning with emphasis on Reinforcement Learning Professor of Research Methodology
Education
April 2022 - March 2026
Universidade Federal do Rio de Janeiro
Field of study
  • Artificial Intelligence
March 2019 - January 2022
Universidade Federal do Rio de Janeiro
Field of study
  • Machine Learning

Publications

Publications (22)
Article
Full-text available
Software development for military organizations follows standards and a set of guidelines established in the requirements engineering domain. However, these procedures are not always documented and it is difficult to reach understanding among stakeholders with varied backgrounds and interests. This article aims to obtain lessons learned through a c...
Book
Todo artigo científico transmite uma mensagem. No entanto, diversos profissionais enfrentam muitas dificuldades ao desenvolvê-lo, como a escolha do método a ser utilizado e o conteúdo a ser escrito. Por exemplo, você pode realizar um experimento extraordinário, mas se não souber como redigi-lo, não obterá êxito. Da mesma forma, você pode escrever b...
Chapter
In this chapter, the most recent applications of Reinforcement Learning (RL) and how this technique impacts various areas of knowledge are explored. Examples of RL applications in areas such as robotics, games, education, and quantum mechanics are presented. In addition, this chapter explores the main benefits and challenges that RL applications pr...
Chapter
This chapter addresses practical tools that help in the development of solutions in Reinforcement Learning (RL). Among them, we highlight some of the main libraries and frameworks available, such as TensorFlow, Keras, and OpenAI Gym, which allow the implementation of RL algorithms more efficiently. Furthermore, some useful data sources for conducti...
Chapter
In this chapter, a case study on the development of an autonomous cab using Artificial Intelligence (AI) in Python is presented. Details of the environment are discussed, and the action of the agent without the use of AI is exemplified. Afterward, the implementation of a Reinforcement Learning (RL) algorithm is presented in a simplified way, commen...
Chapter
This chapter discusses the fundamental concepts needed to understand the entire system involved in Reinforcement Learning. Terms such as agent, environment, actions, rewards, policies, and value function are presented. Examples and analogies are provided to illustrate each of these concepts, from the structuring of problems using the Markov Chain t...
Chapter
This chapter details the operation of the Q-Learning algorithm, one of the most widely used in algorithms Reinforcement Learning. The components of the algorithm and its demonstration through pseudocode are presented. Then, it is explained in detail how the algorithm works, illustrated with a visual example of an agent interacting in an environment...
Chapter
This chapter explores the Artificial Intelligence research area, highlighting the different approaches to Machine Learning and the types of problems that each one solves. The concept of Reinforcement Learning is presented playfully through examples, and its framework is explained in detail. In addition, relevant historical milestones that influence...
Book
Descubra como projetar sistemas inteligentes. Os aplicativos de Inteligência Artificial (IA) trazem agilidade e modernidade para nossas vidas e a técnica de Aprendizagem por Reforço está no ápice dessa tecnologia. Ela é capaz de superar competidores humanos em jogos de estratégia, composições criativas e movimentação autônoma. E só começou a transf...
Article
Full-text available
Technologies that support teachers in exam preparation are explored by academic research and real-life applications. However, few solutions help the teacher identify the complexity of questions. This article introduces the “Intelligent Question Classifier” (CLIQ), a Python Natural Language Processing (NLP) tool for identifying questions complexity...
Article
Full-text available
In recent years some ways of measuring Computer Supported Cooperative Work (CSCW) have been proposed. However, there are few mechanisms for managers to assess the quantitative performance of their teams’ collaboration. This paper presents Collaborizer, a tool designed to benchmark collaborative work based on Agile principles and generate visual rep...
Article
Full-text available
A defense system for geoinformation governance must be able to manage geographic information related to national security. A Geographic Information System (GIS) is useful for the defense of the country, as in the case of monitoring the spread of COVID-19, enabling authorities to make decisions based on data (data-driven). The difficulty in developi...
Article
Full-text available
Deep Learning has been successful in developing e-learning applications, including engineering question classifiers. However, we are not aware of any classification model to date that recognizes the level of difficulty of questions in the Portuguese language. To overcome this challenge, this paper proposes a data-driven classifier model. A corpus w...
Thesis
Data Science has been successful in developing e-learning applications, including engineering of automatic question classifiers. However, studies indicate that there is no classifier model recognizes the level of difficulty of issues in the Portuguese language. To overcome this challenge, this research proposes an automatic question classifier mode...
Article
Full-text available
With the advent of technological evolution, drones have been providing to improve services and operations by their wide range of applications, both in civil and military scopes. In this context, the paper addresses a multicriteria analysis based on the drone assessment to support public security. For the evaluation process, the PROMETHEE-SAPEVO-M1...
Conference Paper
Full-text available
No presente trabalho foi proposta a aplicação do método SAPEVO-M para seleção de equipamentos a serem utilizados para a movimentação de cargas e integração logística intermodal no Exército Brasileiro, com a finalidade de redução do custo agregado e aumento da sustentabilidade da rede de transportes. Concluiu-se que o maquinário selecionado através...
Preprint
A defense system for geoinformation governance must be able to manage geographic information related to national security. A Geographic Information System (GIS) is useful for the defense of the country, as in the case of monitoring the spread of COVID-19, enabling authorities to make informed decisions based on data. The difficulty in developing a...
Conference Paper
Worldwide, the electricity sector has undergone radical changes with the emergence of new technologies that expand possibilities. In such a dynamic environment, the sector's regulatory and supervisory activities became major challenges. In this article, we present a case study on the collaborative design of a digital platform for learning, accessin...

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