Professor at the Federal University of Santa Catarina, Department of Informatics and Statistics.
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.
cross-substrate computationResearch 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.
Computer organization, operating systems, embedded systems, cyber-physical systems, and hardware/software integration.
Modeling and simulation of computational, cyber-physical, educational, and biological systems.
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.
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.
- 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?
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.
- 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?
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.
- 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?
Artificial intelligence for science
Responsible use of modern AI to accelerate literature analysis, modeling, scientific software development, simulation workflows, data interpretation, and academic productivity.
- 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?
Biological computation
Conceptual and computational study of biological substrates as information-processing systems, including biochemical hardware, biological computer organization, and synthetic biological hardware abstractions.
- 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?
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.
- 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.