Computer Science
Phone number: (53) 3284-3860
e-mail: secretaria-ppgc@inf.ufpel.edu.br
Website: http://inf.ufpel.edu.br/ppgc
Address:
Presentation
The Graduate Program in Computer Science was established in 2010 and currently offers a Master’s level degree. The program has well-respected researchers in their field, bringing together a large amount of experience in both teaching and research and working on four research areas: Fundamentals of Computer Science, Parallel and Distributed Processing, Digital and Embedded Systems, and Intelligent Systems.
Aimed toward cutting edge research, the UFPel’s Graduate Program in Computer Science develops high-impact scientific projects regularly funded by major funding agencies. Its faculty and researchers also maintain close relationships with other national and foreign institutions. As a strategic aspect, the developing research seeks to strengthen the cooperative ties with companies and the productive sector in general through both the transfer and creation of knowledge.
Target Audience:
Computer Scientists, Computer Engineers, Electrical Engineers and related professionals.
Area of Concentration
Computer Science
Lines of Research
Line of research: FUNDAMENTALS OF COMPUTER SCIENCE
This line of research focuses on the study of abstract models and theoretical foundations that serve as a basis for the creation of systems and it also develops techniques to ensure correctness in software development.
Topics of interest include: specification, refinement-based construction and verification of software and hardware systems, aiming to achieve higher levels of quality and increase confidence in software correctness through formal testing and refinement; and also the development and analysis of the complexity of computational models applied to the study and analysis of the dynamics of populations and environmental phenomena.
Line of research: PARALLEL AND DISTRIBUTED PROCESSING
This line of research aims to study computational systems designed for parallel or distributed processing. Research efforts focus on the development of execution environments, programming languages and interfaces for such environments. Thus, the topics addressed are linked to the use of special computer architectures, high-performance processing, execution environments, programming languages and mobile and ubiquitous computing.
Applied research is also developed, addressing real problems in the solutions involving the use of parallel and/or distributed systems, as well as issues related to sustainable computing by saving energy in processing through the use of parallel hardware.
Line of research: DIGITAL AND EMBEDDED SYSTEMS
This line of research analyses the conception and design of complex digital systems, including the stages of specification, validation, verification, design, and testing. A major goal of this line of research is to investigate computational systems dedicated to specific applications, which make up the hardware and the software. Design space exploration is also of particular interest to this line of research, in order to find optimized solutions taking into account several commitments such as processing rate and energy and hardware consumption.
The topics covered range from integrated circuit CAD (Computer-Aided Design) techniques to software development and techniques for energy saving in embedded systems.
This line of research also develops algorithms and computer architectures for digital signal, image, and video processing.
Line of research: INTELLIGENT SYSTEMS
This line of research aims to study, develop and implement computer systems capable of solving problems whose solution requires intelligence. It also aims to apply the concepts, techniques and tools of Artificial Intelligence to solve conceptual and practical problems in computing and other areas of knowledge, as well as study and develop state-of-the-art artificial intelligence to be used in industrial processes.
This line of research includes evolving and adapting systems (Evolutionary Systems), distributed intelligence systems (Multiagent Systems), and systems that are able to learn from experience (Machine Learning Systems).
Study Plan
Faculty
Professor Adenauer Corrêa Yamin
http://inf.ufpel.edu.br/adenauer
Professor Aline Loreto
http://inf.ufpel.edu.br/aline
Professor Ana Marilza Pernas
http://inf.ufpel.edu.br/anamarilza
Professor André Du Bois
http://inf.ufpel.edu.br/andre
Professor Bruno Zatt
http://inf.ufpel.edu.br/brunozatt
Professor Denis Franco
http://inf.ufpel.edu.br/denis
Professor Felipe Marques
http://inf.ufpel.edu.br/felipem
Professor Gerson Cavalheiro
http://inf.ufpel.edu.br/gerson
Professor Julio Mattos
http://inf.ufpel.edu.br/julius
Professor Leomar Junior
http://inf.ufpel.edu.br/leomarjr
Professor Lisane Brisolara
http://inf.ufpel.edu.br/lisane
Professor Luciana Foss
http://inf.ufpel.edu.br/luciana
Professor Luciano Agostini
http://inf.ufpel.edu.br/agostini
Professor Marcelo Porto
http://inf.ufpel.edu.br/msporto
Professor Marilton Sanchotene de Aguiar
http://inf.ufpel.edu.br/marilton
Professor Maurício Pilla
http://inf.ufpel.edu.br/pilla
Professor Paulo R. Ferreira Jr.
http://inf.ufpel.edu.br/paulo
Professor Rafael Soares
http://inf.ufpel.edu.br/rafael
Professor Renata Hax Sander Reiser
http://inf.ufpel.edu.br/renata
Professor Ricardo Matsumura Araujo
http://inf.ufpel.edu.br/ricardo
Professor Simone Costa
http://inf.ufpel.edu.br/simone
Number of credits required
24 credits
