Computer science, automation, and systems engineering
Academic formation and teaching activity spanning computer science, automation and systems engineering, computer organization, operating systems, and software/hardware integration.
UFSC · Technological Center · Department of Informatics and Statistics
Prof. Rafael Luiz Cancian, Dr. Ing.
Prof. Rafael Luiz Cancian, Dr. Ing., holds a doctorate in Automation and Systems Engineering, a master's degree in Computer Science, a bachelor's degree in Computer Science, and postgraduate specializations in Political Science, Data Science and Artificial Intelligence, and Financial and Capital Markets.
He is a professor at the Federal University of Santa Catarina (UFSC), with previous higher-education teaching experience at UNIVALI and IFSC and more than a decade of applied work in technology and public-transport consulting.
His academic agenda spans computer architecture and organization, operating systems, digital and embedded systems, modeling and simulation, cyber-physical systems, artificial intelligence, scientific software, and biological computation.
Computing Across Scientific FrontiersSystems
Modeling
Modeling
Computer
Organization
Organization
Digital
Hardware
Hardware
Biological
Computing
Computing
Artificial
Intelligence
Intelligence
Software
Development
Development
Computer
Science
Science
Control &
Automation
Engineering
Automation
Engineering
Political
Science
Science
Financial &
Capital
Markets
Capital
Markets
Data
Science
Science
Academic profile
Computer science, systems engineering, and applied academic leadership.
A compact view of academic formation, professional trajectory, technical competencies, and institutional service.
Modeling and simulation as scientific practice
Research and technological development centered on simulation models, embedded and cyber-physical systems, experimental design, and reproducible scientific software.
Biological computation and whole-system modeling
Long-term research direction connecting biological systems modeling, biological computer organization, BioCAD-like abstractions, and responsible computational communication.
Biography
Systems, software, hardware, simulation, and biological computation.
Prof. Cancian combines university teaching, systems research, scientific software development, and applied technology projects. His formation joins Computer Science with Automation and Systems Engineering, complemented by Data Science and AI, Political Science, and Financial and Capital Markets.
His long-term research vision studies computation as an architecture that can cross substrates: silicon, software systems, cyber-physical platforms, and biological systems. The site communicates that agenda at a conceptual and academic level, without laboratory protocols or operational genetic-engineering instructions.
Competencies
Selected technical and academic areas
Trajectory
Selected academic milestones
Undergraduate formation in Computer Science at UFSC
Foundation in computing, systems, software, and computer architecture, later expanded through graduate research and university teaching.
Master's research in Computer Science
Work on performance evaluation of real-time scheduling algorithms in a multicomputer environment.
Doctorate in Automation and Systems Engineering
Research on multi-objective evolutionary design-space exploration for embedded systems.
Professor at UFSC
Teaching, research, supervision, academic governance, and technological work across systems, simulation, AI, and biological computation.
Academic service
Institutional and governance activities
Selected activities in course coordination, university governance, curriculum boards, laboratory coordination, research, and extension leadership.
Internship coordinator, Computer Science at UFSC
Coordinates internship activities for the Computer Science program, connecting students, course requirements, and professional practice.
Coordinator, Computer Science program at UFSC
Served as coordinator of the Computer Science undergraduate program and represented the program in university-level undergraduate governance.
Course boards, councils, and laboratory coordination
Participated in UFSC academic governance, course boards, and software/hardware integration laboratory coordination.
Research identity
Integrated systems, simulation, AI, and biological computation.
A compact academic identity connects computer architecture, operating systems, digital and embedded systems, modeling and simulation, AI-assisted scientific computing, and biological computation.
Computing systems as engineered organizations
From digital systems and processor organization to hardware/software integration, architecture is treated as abstraction, composition, and constraint-aware design.
Operating systems, embedded platforms, and cyber-physical design
Systems software and embedded platforms connect resource management, runtime behavior, and application-oriented engineering.
Modeling as an experimental instrument
Simulation is used as a reusable method for studying computational systems, biological systems, educational systems, and decision-support workflows.
Computation beyond silicon
The BioCompLab bridge positions biological substrates, synthetic biological hardware, and whole-cell simulation as computational research objects.
Selected areas
Research areas
The following cards summarize the conceptual structure of the research agenda and connect classical computer systems topics to biological and AI-assisted scientific computing.
Established
Computer architecture and organization
Study of computational structures, reusable hardware components, application-specific processors, and the bridge between hardware design methods and software engineering principles.
Research questions
- How should computer organization be taught and modeled across abstraction levels?
- How can reusable hardware components be integrated into systematic design workflows?
- What changes when architecture is treated as a cross-substrate concept?
Established
Operating systems and systems software
Operating systems, runtime infrastructure, embedded systems software, real-time scheduling, and systems-level abstractions for dedicated computing platforms.
Research questions
- Which abstractions remain useful in deeply embedded or dedicated systems?
- How can systems software become more reusable without losing performance?
- How should hardware/software co-design influence operating-system architecture?
Active
Modeling and simulation of systems
Modeling and simulation as a scientific and engineering method, spanning discrete-event simulation, stochastic models, cellular automata, continuous models, and simulation tooling.
Research questions
- How can simulation tools remain generic while supporting domain-specific model components?
- How can experimental design and statistical analysis be integrated into simulation platforms?
- How can simulation support education, software engineering, and biological systems modeling?
Emerging
Artificial intelligence for science
Responsible use of modern AI to accelerate literature analysis, modeling, scientific software development, simulation workflows, data interpretation, and academic productivity.
Research questions
- Which parts of scientific software engineering can be safely automated with AI assistance?
- How can AI agents support reproducible modeling and simulation workflows?
- How should research groups govern AI usage without weakening scientific rigor?
Active
Biological computation
Conceptual and computational study of biological substrates as information-processing systems, including biochemical hardware and biological computer organization.
Research questions
- Can computer organization concepts be mapped to biochemical and biological substrates?
- What would an execution unit or processor mean when the substrate is biomolecular?
- Which abstractions are useful before any physical biological implementation is attempted?
Long-term agenda
Synthetic biology and systems biology
High-level computational study of synthetic and systems biology problems, emphasizing modeling, responsible communication, and abstractions for biological systems design.
Research questions
- How can systems biology models support safer conceptual evaluation of synthetic systems?
- Which computational abstractions are suitable for biological design automation?
- How can research communication remain ambitious without overclaiming biological feasibility?
Contact
Academic contact and profiles
Institutional affiliation
Professor, Department of Informatics and Statistics, Federal University of Santa Catarina
Florianópolis, Santa Catarina, Brazil