Research profile
Computational intelligence for dependable physical systems.
Đỗ Quốc Trọng is developing an independent research programme through CIES Laboratory, focused on computational intelligence, embedded electrical systems, and autonomy.
The programme is presently at a formative stage. Its purpose is to turn well-defined research questions into documented prototypes, reproducible experiments, and public research outputs. Statements on this page distinguish current facts from intended future work.
Research interests
Current role and scope
CIES Laboratory is an independently operated research initiative and is not currently represented as a university department, accredited institution, registered nonprofit research institute, or degree-granting body.
Developing a public foundation for future work in computation and electrical systems through documented prototypes and open research practices.
Proposed research agenda
The planned agenda focuses on resource-aware intelligence, trustworthy autonomy, smart sensing, and the co-design of algorithms with the hardware and physical environments in which they operate. These themes describe intended work, not completed or funded projects.
Research approach
The programme uses a systems-oriented approach: research questions are translated into measurable prototypes, evaluated under real resource constraints, and documented with explicit limitations. Particular attention is given to latency, energy, memory, uncertainty, safety, and the interaction between algorithms and physical devices.
Public evidence register
| Evidence area | Current record | Publication rule |
|---|---|---|
| Researcher identity | Open Name and independent role published on this domain | Add a real ORCID only after registration and ownership verification |
| Institutional affiliation | Not present No accredited or nonprofit institute affiliation claimed | Add only with a public institutional directory and appointment record |
| Peer-reviewed publications | Not present No publication claim currently made | Add DOI, venue, author list, and publisher record together |
| Preprints | Planned First original manuscript not yet released | Add only through a recognized repository with a persistent identifier |
| Research software | Planned Public repository and archived release pending | Link source, license, documentation, release tag, and archive DOI |
| Datasets and protocols | Planned No public dataset currently listed | Provide provenance, license, methods, limitations, and persistent identifier |
| Funding and grants | Not present No funded grant claimed | Add only with an official funder award page or executed agreement |
Research-output standard
- Every project receives a clear question, hypothesis, baseline, evaluation protocol, and limitations statement.
- Public claims link to primary evidence rather than self-authored summaries alone.
- Code releases include a license, environment instructions, versioned results, and an archived snapshot.
- Datasets include provenance, consent or collection basis where applicable, intended use, and known limitations.
- Corrections, negative results, and changes to project status remain visible.
Profile completion milestones
- Research identity: register a real ORCID and connect it to consistent name metadata.
- First public output: complete an original study and release a reproducible preprint, codebase, or dataset.
- Independent corroboration: obtain records hosted by repositories, publishers, funders, or collaborators outside this domain.
- Genuine affiliation: pursue a documented research collaboration or appointment with an eligible university or nonprofit research institute.
- Programme application: apply only when every eligibility statement can be independently verified.
A custom domain and organizational email help establish a professional web presence, but they do not replace research outputs, institutional affiliation, or third-party verification.
Research enquiries
Relevant enquiries include interdisciplinary concept studies, prototype evaluation, edge-intelligence experiments, embedded sensing, safe autonomy, and research tooling. Contact trong.do@cieslab.science.