Model before claiming implementation
Research communication emphasizes models, abstractions, simulation assumptions, and validation boundaries before any claim about physical or biological feasibility.
Research
Computer systems research extended toward biological computation.
The research agenda connects established computer science topics with long-term questions about computation beyond conventional silicon substrates.
Method
How the research agenda is framed
The research pages are structured to support precise academic communication without overclaiming maturity or implementation status.
Architectural continuity across substrates
Classical systems concepts—execution, memory, interconnects, scheduling, components, and design spaces—are treated as reusable analytical lenses.
Scientific software as infrastructure
Simulators, design-support tools, and AI-assisted workflows are considered part of the research method, not merely auxiliary implementation artifacts.
Research profile
More context behind the research agenda
The following notes expand the public research profile using curated information from the Lattes record and the public LinkedIn profile, without reproducing a complete CV.
From computer systems to biological substrates
The research line starts from classical systems topics—computer organization, operating systems, embedded systems, real-time scheduling, and hardware/software integration—and extends them toward biological computation and biochemical hardware abstractions.
- Doctoral work in design-space exploration for embedded systems.
- Long-term work with modeling and simulation as a scientific and engineering method.
- Current emphasis on biological computation, synthetic biological hardware, and whole-cell simulation as conceptual and computational research objects.
Simulation before claims of implementation
The website should make explicit that computational models, simulation frameworks, and architectural abstractions are not the same as deployed biological implementations. This distinction is central to responsible communication in biological computing.
- Use explicit maturity labels: established, active, emerging, long-term agenda.
- Prefer model validity, reproducibility, and traceability over speculative claims.
- Keep synthetic biology content conceptual and computational, without operational wet-lab guidance.
Scientific software and applied systems engineering
The public profile also supports collaboration in software-intensive research: web systems, mobile applications, data analysis, software testing, project management, and custom scientific tooling.
- Useful for applied research prototypes and student-led software projects.
- Compatible with future repository links, demonstrators, and reproducible simulation artifacts.
- Connects academic research with practical engineering constraints.
Areas
Research areas and questions
Each area includes a short description, representative questions, and collaboration vectors.
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?
Emerging
Whole-cell simulation
Simulation of cellular-scale behavior as a prerequisite for evaluating how biological systems could act as target substrates for digital or computational functions.
Research questions
- Which cellular models are sufficient for evaluating system-level computational behavior?
- How can whole-cell simulation be made modular, extensible, and scientifically auditable?
- Which levels of abstraction are appropriate for academic communication and tool development?
Long-term agenda
Biological computer architecture
A research agenda that asks how classical computer architecture ideas—execution units, processors, memories, interconnects, instructions and design flows—could be reinterpreted across biological substrates.
Research questions
- What is the biological analogue of a reusable hardware component?
- Can design-space exploration be generalized beyond silicon-based platforms?
- How should architecture curricula and research adapt to nontraditional substrates?