Graduate Program in Informatics
The Graduate Program in Informatics (PPGIa) completed 24 years in 2020. The master’s program was conceived in August 1996 and obtained a recommendation from CAPES in 1997, becoming the first master’s program in Informatics in Paraná. The doctoral program was created in 1998 and was recommended by CAPES in 2006 in the computer science doctoral field.
The Doctoral program has a CAPES evaluation rating of 5, with 40% of its faculty recognized as researchers with productivity grants by CNPq. The majority (95%) of students have tuition exemption or scholarships.
Objectives
- Promote scientific and technological research in complex environments (multidisciplinary and interdisciplinary)
- Educate highly qualified professionals to work in sophisticated research, development, and innovation activities
History
The Graduate Program in Informatics (PPGIa), with a concentration area in Computer Science, celebrated 24 years of existence in 2020. The master’s program was conceived in August 1996. The following year, it obtained the CAPES recommendation, becoming the first master’s program in informatics in Paraná. By 2019, PPGIa counted 333 master’s theses. The doctoral program was created in 1998 and recommended by CAPES in 2006.
Master’s program
- August 1996: First class conducted
- 1997: Received CAPES recommendation
- November 1998: First thesis defended
- August 2004: 100th thesis defended
- 2018: Reached Level 5
- February 2020: Approximately 350 master’s dissertations defended
Doctoral program
- August 1998: First class conducted
- November 2001: First dissertation defended.
- 2006: Received CAPES recommendation
- February 2020: Approximately 80 theses defended
Mission
The Graduate Program in Informatics aims to produce and disseminate scientific and technological knowledge in computer science, promoting the education of ethical professionals committed to the development of science and society’s progress.
Vision
- To achieve national and international recognition for excellence in scientific production and innovative solutions promoting society’s transformation
Goals
- Promote scientific and technological progress aiming social well-being
- Educate highly qualified researchers, attuned to the needs of society and industry
- Act at the forefront of teaching and learning to conceive outstanding professionals for society
- Achieve an international excellence level in the development of scientific research in informatics and the education of researchers
Organizational structure
PPGIa is subordinate to the Polytechnic School and the Research, Graduate Studies, and Innovation Office at PUCPR. Internally, the program has the following organizations:
- Council: Composed of permanent program faculty, undergraduate program coordinators in Computer Science, Computer Engineering and Information Systems, and student representatives from Master’s and Doctoral programs
- Program Director: Appointed by the Research, Graduate Studies, and Innovations Office
- Committees: Teaching Committee, Admission and Scholarship Committee, and SUCUPIRA Committee.
PPGIa Council
PPGIa council is composed of all of the program’s permanent faculty members, the directors of the undergraduate programs in Computer Science, Computer Engineering and Information Systems, and two student representatives, one from the master’s program and one from the doctoral program.
PPGIa Committees
PPGIa has several committees formed by its faculty to assist the program‘s academic administration of the. There are currently four committees, as follows.
Teaching Committee
This committee is composed by the PPGIa research group leaders. Thus, it is responsible for evaluating requests from PPGIa students and faculty.
- Altair Olivo Santin
- Júlio Cesar Nievola—rapporteur
- Marcelo Eduardo Pellenz
- Sheila Reinehr
Admission and Scholarship Committee
This committee is responsible for the admission process and awarding scholarships to incoming students of the master’s and doctoral programs.
- Alceu de Souza Britto Jr.
- Andreia Malucelli
- Edson Emílio Scalabrin
- Emerson Cabrera Paraiso — rapporteur
- Marcelo Eduardo Pellenz
DATACAPES Committee
This committee is responsible for completing and reviewing PPGIa information passed on to CAPES’ Sucupira Platform for the annual and four-year evaluations.
- Emerson Cabrera Paraiso
- Fabricio Enembreck — rapporteur
- Marcelo Eduardo Pellenz
- Sheila Reinehr
Alumni Profile
Master’s program: Develop research of scientific, technological, and social impact, both nationally and internationally, ethically, and collaboratively.
Doctoral program: Offer and develop interdisciplinary research of high scientific, technological, and social impact, both nationally and internationally, in an ethical, collaborative, and autonomous way.
Computer science
Data Science
Data science is an interdisciplinary area that studies where data (structured or not) originates, what they represent, and how to extract the knowledge they contain to assist in decision-making processes. It uses concepts and algorithms from statistics, artificial intelligence, machine learning, and data mining to solve complex problems. Data science is considered a process covering several phases, such as problem definition, data collection, data preparation, data pre-processing, selection of the knowledge extraction algorithm and its parameters, training, and validation of the generated model, in addition to the continuous evaluation of the process as a whole.
Systems Engineering
Systems engineering is an interdisciplinary area that comprises innovation in computer systems architecture, methods, and techniques. The research area works vertically in hardware and software engineering with integration and intelligence. It involves the processes and methods for development in several fields such as pattern recognition, machine learning, computer security, and telecommunications. This field’s challenges are the computer science and computer engineering complex relationships, involving hardware and software, which demand high-performance processing with Big Data, IoT devices, cloud computing, wired and wireless communication systems, applying process control, and computational security. Systems engineering is at the heart of the research, development, and innovation ecosystem of smart cities and the 4th generation Industrial Revolution.
Artificial intelligence
Artificial intelligence as a technological enterprise has made possible, based on recent results regarding knowledge representation, machine learning and reasoning with imperfect information, the construction of useful products and artifacts (e.g., mobile robotics, search engines, and product recommendations). Artificial intelligence as a research area is quite broad, including crucial subjects such as machine learning, knowledge representation, planning, reasoning, restrictions satisfaction, natural language processing, and multi-agent systems. Research contributions can be theoretical, technical, and applied. Applied research also advances in AI techniques in the context of new areas, such as cybersecurity, sustainability, healthcare, human well-being, transport, trade, and industry 4.0.
PPGIa has an exclusive infrastructure for the program:
- Research and development laboratories
- Faculty offices
- Administrative office
- Student offices
- Computing support lab
- Printer room
- Meeting Room
- Four classrooms with 40 seats each
- Study room
The PPGIa facilities occupy around 950 m2 in Block II of the PUCPR Technological Park—Curitiba Campus. The following laboratories are part of the PPGIa research groups:
- Intelligent Systems Lab
- Distributed Systems Lab
- Computer Security and Privacy Lab
- Software Agents Lab
- Computer Vision Lab
- Software Engineering Lab
PPGIa students have full access to the Internet, both locally (labs) and remotely (residential), via the institution’s servers. PUCPR’s main campus is covered by an internet backbone that guarantees speed and quality of information access.
PPGIa has its internal network, focused on meeting differentiated needs of research and development activities. This network provides multiple servers, a high-performance processing cluster, high-quality printers, and other resources.
The computer park at PUCPR is continuously updated, both exclusively for PPGIa students and in other facilities at the Curitiba Campus.
Besides computational resources, there are several audiovisual resources available (multimedia projectors, projection rooms) to students, which enable excellent presentations of research progress seminars.
The program has several initiatives underway to expand its internationalization. Furthermore, PUCPR has been dedicating itself intensely to this objective through the International Relations Office, including the following:
- Activities developed inside the university, such as receiving visiting professors and students
- Courses taught in English, as well as outside the country, aiming to make the institution known and recognized outside Brazil (such as the availability of the material in English)
- International event participation by students, faculty and administrators
- Dual degrees at different levels
- Co-supervision
Every year, PPGIa receives visiting professors, financed by its own resources.
PPGIa has encouraged students to write their master’s theses and doctoral dissertations in English. Thus, defense committees with international members’ participation are made possible with visiting professors or even held by video conference. This initiative also increases the possibility of disseminating the research.
In 2020, two courses were offered in English (Advanced Topics in Computational Intelligence and Data Science), encouraging students to develop communication skills in English as well as receive international students.
Several students had foreign co-supervisors.
Faculty also give invited lectures at institutions abroad, such as Dr. Alceu de Souza Britto Jr., who lectured at the University of Rouen, France (Title: Dynamic Selection of Classifiers based on Complexity Measures).
Some faculty also participated as external members on defense committees abroad.
Currently, several international research projects are underway, including the following highlights:
- The research project for sound type classification (songs, birds, whales) in partnership with researchers Dr. Loris Nanni – University of Padova, Italy; Dr. Sheryl Brahnam – Missouri State University (USA); and Dr. Yandre Maldonado Gomes e Costa – Maringá State University
- The research project for emotion classification and listening tests in partnership with Dr. Xiao Hu – University of Hong Kong
- Project for automatic classification of signals for prosthesis control in partnership with Dr. Adam Arabian from Seattle Pacific University (USA).
- The Paris Saclay Research Project – Albert Bifet – scientific collaboration; Waikato University – Bernhard Phfaringer – scientific collaboration
- Research Project in the Area of Environmental Networks – Faculty of Technology – University of Portsmouth Wireless Network Projects; Pierre and Marie Curie University, France – Dr. Guy Pujolle
- Resilient Supervision and Control in Smart Grids project, University of Lisbon – InMetro. CAPES-FCT funding
- The FIGTEM Project: FineGrained Text Mining for Clinical Trials, with Dr. Vincent Claveau – IRISA – Rennes, France, Natalia Grabar – University of Lille, France, Claudia Moro PPGTS/PUCPR and Emerson Cabrera Paraiso
- The project: A Framework for Facilitating the Development of Systems, in partnership with Dr. Jean-Paul Barthès & Dr. Marie-Helene Abel – University of Technology, Compiègne, France
- The project: The Impact of Complexity Measures on Dynamic Classifier Selection Based Methods, in partnership with Dr. Robert Sabourin from ÉTS, Canada
- The Robust Feature Representation for Computer Vision Problem project – CAPES/FA, PUCPR – Federal University of Pernambuco (Brazil) and University of Rouen (France)
- Dr. Santin has a CAPES-FCT project — Resilient Supervision and Control in Smart Grids — with the University of Lisbon.
- In 2018, the PPGIa had a co-supervised student, Roni Shigueta, from the University of Paris-Saclay.
To disseminate research developed at the institution and allow the student body to participate in international events, PUCPR has an internal policy that allows student participation funding in scientific events for paper presentations.
Faculty members have also presented papers internationally, such as at events listed below.
PPGIa has several research projects in progress divided among the program research areas. The projects include scientific initiation, master’s, doctoral, and post-doctoral students. Several projects involve the participation of researchers from international institutions. Moreover, many projects are undertaken using resources from development agencies and private companies.
Faculty
Alceu de Souza Britto Jr.
Dr., Pontifical Catholic University of Paraná, 2001
Researcher with CNPq Productivity Grant
Image Processing, Pattern Recognition
Altair Olivo Santin
Dr., Federal University of Santa Catarina, Brazil, 2004
Researcher with CNPq Productivity in Technological Development and Innovative Extension Grant
IEEE, ACM, SBC, CREAPR member
Authentication, Authorization, and Auditing in Distributed Systems, Models, Policies, and Security Mechanisms, Public Key Infrastructure
Andreia Malucelli
Dr., University of Porto (Portugal), 2006
Researcher with CNPq Productivity Grant
SBC member. Organizational Learning, Business Intelligence, Software Agents, and Ontologies applied to Software Engineering
Carlos Nascimento Silla Junior
Dr., University of Kent, Inglaterra, 2011
Researcher with CNPq Productivity Grant
Data Mining, Computational Intelligence, Music Information Retrieval, Computer Music Technology
Edson Emílio Scalabrin
Dr., University of Technology of Compiègne, France, 1996
SBC member. E-Negotiation, E-Marketplace, Reputation Management for E-Service, Multi-Agent System, Autonomous Agents, Distributed Planning
Eduardo Kugler Viegas
Dr., Pontifical Catholic University of Paraná, 2018
CyberSecurity, Computer Security, Intrusion Detection, Machine Learning for Security, Big Data and IoT Security, Applied Cryptography, Computer Forensics
Emerson Cabrera Paraiso
Dr., University of Technology of Compiègne, France, 2005
ACM, IEEE, SBC member. Human-Computer Interaction, Natural Language Processing, Text Mining, Affective Computing
Fabrício Enembreck
Dr., University of Technology of Compiègne, France, 2003
Researcher with CNPq Productivity Grant
Multi-Agent System, Adaptive Agents, Data Mining
Jean Paul Barddal
Dr., Pontifical Catholic University of Paraná, 2018
Data mining and machine learning focused on streaming data, classification, regression, concept drift, feature selection, and clustering
Júlio Cesar Nievola
Dr., Federal University of Santa Catarina, Brazil, 1995
Researcher with Araucária Foundation Productivity Grant
IEEE, ACM member. Data Mining, Intelligent Systems, Artificial Neural Networks
Marcelo Eduardo Pellenz
Dr., State University of Campinas, 2000
Researcher with CNPq Productivity Grant
Digital Transmission, Wireless Networks, Sensor Networks, Traffic Modeling, Modeling and Simulation of Performance in Wireless Networks, Channel Coding, and Source Coding
Sheila Reinehr
Dr., São Paulo University, 2008
Researcher with CNPq Productivity Grant
SBC member. Software Quality, Software Process Improvement, Software Metrics, and Project Management
Courses
Advanced Topics in Computational Intelligence
Multi-label classification; Hierarchical Classification; DataStream mining: concepts, classification, regression, and grouping methods; Concept and detectors changing; Reinforcement learning. Prerequisite courses: Data Mining and Machine Learning Assessment: Writing of a paper. Please note: The course will be taught in English.
Credits: 2
Software Agents
Multi-agent systems, general principles, and applications; Autonomous agents and multi-agent systems; Introduction to distributed problem solving. Cooperation, coordination, and negotiation; Agent’s communication; Communication architectures; Communication content languages; Interaction protocols; Agent models and architectures; Taxonomy of Agents; Autonomous, reactive, deliberative, and adaptive agents; AUML.
Credits: 2
Machine Learning
Introduction; Concept Learning; Learning with Decision Trees; Bayesian Learning; Instance-Based Learning; Neural Networks Learning; Unsupervised Learning; Hypothesis Evaluation; Selected Topics.
Credits: 2
From Natural Language to Information
Definition of Natural Language Processing, Information Retrieval, Computational Linguistics; Basic text processing operations; Regular Expressions; The Similarity between Texts; Lexical Ontology. Information Extraction and Retrieval; Text Mining; Text classification; Sentiment Analysis.
Credits: 2
Data Science
Basic statistics: distributions, kurtosis, and symmetry; Correlations: Pearson and spearman; Data Visualization; Exploratory Data Analysis: univariate and multivariate data analysis; Identification and treatment of missing values; Identification of outliers; Dimensionality reduction: PCA and t-SNE.
Credits: 2
Statistics
Statistics concepts; Descriptive Statistics; Parametric tests using Excel; SPSS: concepts, descriptive, and tests; Parametric and nonparametric tests on two variables; Parametric and nonparametric tests on three or more variables; Correlation and regression, simple and multiple; Topics in Multivariate Statistics.
Credits: 2
Fundamentals of Algorithms and Data Structure
Basic Concepts: Role of algorithms in computing; Recurrence, Complexity; Sorting Methods, Elementary Data Structures (lists, stacks, queues), and Hash Tables; Binary trees, balanced trees: AVL and red-black; Advanced structures: heaps, tries, and PATRICIA trees; Graphs; Simple algorithms, walks, shortest paths, flow networks, maximum flow, and the Ford-Fulkerson algorithm; Advanced topics, dynamic programming, greedy algorithms, string matching, and NP-completeness.
Credits: 2
Big Data Fundamentals
Big Data Ecosystems; Distributed Storage; Batch Processing; MapReduce; Apache Spark; Apache Spark SQL; Distributed Machine Learning; Apache MLib.
Credits: 2
IoT Fundamentals
IoT fundamentals; Devices; Processing architecture; Protocols; Applications.
Credits: 2
Fundamentals of Computational Mathematics
Numerical solution of linear systems of equations: Gauss’s elimination, iterative methods (e.g., Jacobi and Gauss-Seidel); Rounding error, pivoting, and poorly conditioned systems; Polynomial interpolation and numerical integration; Truncation error analysis and numerical conditioning; Numerical methods for solving ordinary differential equations.; Explicit and implicit methods and single step as well as multi-step methods; Tests and computational modeling of probability and statistical functions.
Credits: 2
Artificial Intelligence
Introduction to problem-solving, Search Algorithms, Heuristic Search, Best First, A * and AND/OR Graphs; Expert systems; Progressive and regressive reasoning; Introduction to Machine Learning and symbolic learning algorithms. Planning.
Credits: 2
Computing Research Methodology
Paradigms in Science; Methods and Knowledge; Problems, Hypotheses, and Evaluation of Projects in Computing; Standards to produce scientific documents and papers.
Credits: 2
Data Mining
Introduction to data mining: objectives and main characteristics; Data mining tasks: classification, clustering, association, and the discovery of scientific laws; Discovery of association rules: basic algorithms.
Credits: 2
Programming Language Paradigms
Logical Programming, Functional Programming, Object-Oriented Programming, Object-Oriented Programming Languages, Introduction to object-oriented modeling in UML.
Credits: 2
Software quality
Fundamentals of Software Quality; IT Governance Models; Software Quality Standards and Models; Software Product and Process Quality Assurance; Techniques of Quality Evaluation; Software Product and Process Measurements.
Credits: 2
Wireless Communication Networks
Introduction to Wireless Communications; Small and Large-Scale Propagation Models; Theoretical Limits for Channel Capacity, Digital Transmission Schemes and Performance Metrics; Diversity Techniques and Multiple-Access Strategies; Wireless Network Transmission Capacity; Emerging Technologies; Protocols and Applications in the Wireless Communication Area: Internet of Things (IoT); Smart Grids; Smart Cities; Wireless Sensor Networks and 4G/5G Systems.
Credits: 2
Computer Systems Security
(In)security scenarios; Fundamentals of Computational Security: Properties, Policies, Violations; Models, Services and Mechanisms for Authentication and Access Control; Cryptographic Controls: Cryptographic Systems, Digital Signature, Key Management, PKI (Public Key Infrastructure); Security in Distributed Systems: Authentication, Authorization, Access Control, and Policies; Case Studies—computer systems security technologies.
Credits: 2
More Information
Click below to access the public notice describing the degree requirements (in Portuguese).
PPGIa has contributed to the training of qualified human resources who work in various sectors with social influence: education, government agencies, and industry.
PPGIa works in several projects with social integration, including the following:
- The MR-MPS-SV model, currently operated by SOFTEX, was derived from a master’s thesis defended at PPGIa in 2011. In all, 45 official assessments have already been conducted in national and foreign companies. In 2017, there were 11 assessments, representing 30% growth over the previous year. The use has received national coverage with companies in the northeast, central west, southeast, and south regions.
The project with Nokia to create IoT pilots for agribusiness and smart cities in Brazil – http://www.telesintese.com.br/nokia-cria-pilotos-de-iot-para-agrobusiness-e-cidades-inteligentes-no-Brazil/ (in Portuguese).
- A project for developing an application to help diabetes treatment in adolescents, in partnership with researchers from the Federal University of Minas Gerais
- New Technologies Project to Support the Implementation of Law No. 11,769 (Law of Music in Schools).
- Project “MCTI/CNPq/CT-ENERG: Authentication and Distributed Authorization, based on Computational Cloud, for Smart Grid” aims to protect the security and privacy of the electrical system users.
Some relevant papers already published:
- S. Parpinelli; H.S. Lopes; A. A. Freitas. “Data mining with an ant colony optimization algorithm,” IEEE Transactions on Evolutionary Computation—6:4, 2002.
- Justino; F. Bortolozzi; R. Sabourin. “A comparison of SVM and HMM classifiers in the off-line signature verification,” Pattern Recognition Letters, 26:9, 2005.
- N. Silla JR.; A. A. Freitas. “A survey of hierarchical classification across different application domains.” DATA MINING AND KNOWLEDGE DISCOVERY, v. 22, p. 31-72, 2011.
Since 2011, PUCPR has engaged in a project called Excellence in Stricto Sensu that is aimed at internationalizing the institution’s programs to achieve maximum scores of 6 and 7 and to promote transdisciplinarity and innovation in different areas of knowledge, especially in its strategic areas. The PIBIC master program is one its greatest differentials (it allows talented students to attend both undergraduate and graduate stricto sensu programs and develop part of their research in a highly qualified foreign institution) as well as being in harmony with society and focusing on innovation.
The institution must also be constantly attentive to the changing needs of the society, with alignment/realignment to the CAPES criteria and oriented to develop internationally, having internationalization as its main guide in the search for quality in teaching and research.
Every graduate program must meet the criteria set by their corresponding committee; therefore, each program strategic planning and operating criteria needs to be done accordingly.
Criteria for each area need to be discussed within the program annually so that all necessary and appropriate corrective actions can be taken during the four-year period. Each program is committed to structuring and readjusting its strategic planning annually in search of excellence. In addition, the programs are encouraged to rethink their lines of research in order to adapt to the rapid changes that may occur in international and national scenarios.
This graduate program’s dynamism and flexibility must always meet quality criterion both in master’s and doctoral training and in the development of research and innovation, essentially aiming at the improvement of society. Thus, an annual review of each program strategic planning is requested that contains the topics below at a minimum:
- i. Mission and vision of the program;
- ii. Summarized annual opinion produced by an external evaluator; the annual evaluation by an external member is an institutional practice conducted since 2006, which allows for the annual performance of each program to be assessed according to the area criteria;
- iii. Strengths, weaknesses, opportunities, and risks (preparation of a SWOT matrix showing external and internal factors) considering the goals for the current and next four years;
- iv. Goals (measurable objectives) established for the consolidation and development of strengths and improvement of weaknesses;
- v. Actions (processes) necessary to achieve the objectives, people in charge, and monitoring instruments; in this topic, the coordinator and the institution should get involved to consider resizing the faculty and the student body, criteria for accreditation/re-accreditation, infrastructure, selection process, strategies to increase fundraising, and citations and innovation, among other items;
- vi. Preliminary text of the program’s self-assessment describing the last four years containing at least the following information: stages of the self-assessment process; analysis of results and achievement of objectives; necessary actions for its consolidation and internationalization;
The IDP (Institutional Development Plan) document presents the strategic plans of all the programs aligned with the institutional planning, containing the Mission, Vision, SWOT Matrix, Canvas, and road map, and providing information on the needs and intentions of the programs for the 2017–2020 and 2021–2024 quadrennium of the CAPES evaluation.