UFSC · Computer Science · Systems · Biological Computation

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.

Professor, Department of Informatics and Statistics, Federal University of Santa CatarinaFlorianópolis, Santa Catarina, BrazilCANCIAN, R. L.
Selective academic profile · verified metadata only · responsible biological computing communication
Portrait of Prof. Rafael Luiz Canciancross-substrate computation
architecture
AI
DNA
software
systems
digital

Research identity

A systems view of computation across substrates.

The website emphasizes selected academic themes rather than reproducing the full Lattes record: systems, architecture, modeling, simulation, AI-assisted research, and biological computation.

2011–UFSC faculty

Professor at the Federal University of Santa Catarina, Department of Informatics and Statistics.

systemsCore discipline

Computer organization, operating systems, embedded systems, cyber-physical systems, and hardware/software integration.

simulationMethodological axis

Modeling and simulation of computational, cyber-physical, educational, and biological systems.

bio + computeLong-term agenda

Biological computation, systems biology, synthetic biology, 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 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?
  • architecture
  • hardware
  • digital systems
  • CAD
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?
  • OS
  • runtime
  • embedded
  • real-time
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?
  • simulation
  • discrete events
  • models
  • systems
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?
  • AI
  • agents
  • automation
  • research workflows
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?
  • biocomputation
  • biochemical hardware
  • systems biology
  • architecture
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?
  • synthetic biology
  • systems biology
  • responsible research
  • models

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.

01 / architecture

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.

02 / systems

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.

03 / simulation

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.

04 / biological computation

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.

2019–presentActive

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.

  • biological computation
  • simulation
  • BioCAD
  • digital circuits
2019–presentActive

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.

  • simulation
  • scientific software
  • discrete-event
  • modeling
2011–2016Inactive

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.

  • cyber-physical systems
  • optimization
  • embedded systems
  • design automation

Fast access

Quick links