Professor at the Federal University of Santa Catarina, Department of Informatics and Statistics.
UFSC · Technologial Center. Department of Computer Science
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 has been an associate professor in the Department of Computing at the Federal University of Santa Catarina (UFSC) for more than 15 years, previously taught in higher education at UNIVALI and IFSC for more than 10 years, and also served for more than a decade as a partner-director of a small consulting company in urban public transportation and information technology.
He has been a member of the Brazilian Society for the Advancement of Science (SBPC) for more than 20 years and a member of the Brazilian Computer Society for about 20 years. His experience spans automation engineering, computer engineering, and computer science, with emphasis on software/hardware integration and systems simulation. His research, outreach, and technological development agenda focuses on biological and biochemical computing, artificial intelligence, system modeling and simulation, cyber-physical systems, and computer organization.
Selective academic profile · verified metadata only · responsible biological computing communication
cross-substrate computationarchitecture
AI
DNA
software
systems
digital
Research identity
Computer architecture, AI, and biological computation.
Computer scientist and systems engineer working at the intersection of computer architecture, operating systems, modeling and simulation, artificial intelligence, biological computation, and responsible scientific software.
Reviewed Lattes record includes journal papers, a book, a book chapter, and complete conference papers.
Undergraduate final projects, scientific initiation projects, and extension-oriented student work.
Computer organization, operating systems, embedded and cyber-physical systems, simulation, and biological computation.
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 conceptual 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, reusable system components, 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 general scientific and engineering method, spanning discrete-event simulation, stochastic models, cellular automata, continuous models, experimental design, 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, biological computer organization, and synthetic biological hardware abstractions.
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 scientific communication, and abstractions for biological systems design without operational wet-lab protocols.
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?
Research vectors
One academic identity, four connected technical axes.
The public site should make the intellectual structure clear without becoming a database dump. These vectors guide the homepage, research page, supervision page, and future repository links.
Computing systems as engineered organizations
From digital systems and processor organization to hardware/software integration, the site frames architecture as a discipline of abstraction, composition, and constraint-aware design.
Operating systems, embedded platforms, and cyber-physical design
The academic narrative connects operating-system components, embedded platforms, design-space exploration, and application-oriented systems engineering.
Modeling as an experimental instrument
Simulation is presented as a reusable scientific method for studying computational systems, biological systems, educational systems, and decision-support workflows.
Computation beyond silicon
The BioCompLab bridge is positioned as a research agenda on biological substrates, synthetic biological hardware, and responsible scientific communication.
Editorial boundary
Clear about what the site is—and what it is not.
- This is a selective academic website, not a complete CV database.
- Publications are not listed unless DOI, URL, repository, or confirmed metadata are available.
- Biological computation is described conceptually and institutionally; the site does not provide wet-lab protocols or operational genetic-engineering procedures.
- Projects are marked as active, completed, planned, or research agenda items to avoid overstating their status.
Current signals
Selected project directions
A compact view of active, historical, and planned initiatives. Project pages can later be connected to repositories, public reports, or CMS-managed records.
Biological systems simulation models for physical synthesis of digital circuits in bacteria
Research project centered on simulation models capable of representing unicellular biological systems as target substrates for the physical synthesis of digital circuits. The website presents this as a computational and modeling agenda, not as a biological protocol.
GenESys — Reborn Generic and Expansible System Simulator
A modular and extensible system simulator oriented to discrete-event simulation, time-driven models, stochastic processes, cellular automata, continuous models, statistical analysis, experimental design, and future parallel/distributed simulation support.
ADESDToolSuite — Application-directed cyber-physical systems design automation
Tool suite related to automated design and generation of cyber-physical systems, design-space exploration, multi-objective evolutionary optimization, and hardware/software platform modeling.
Fast access
Quick links
Academic profile
Biography, institutional role, and scientific vision.
Research
Research agenda across systems and biological computation.
Projects
Research, technological development, extension, and planned work.
Teaching
Courses, teaching areas, and future material structure.
Publications
Metadata-ready page for verified publication records.