# Tomáš Báča

> researcher (ORCID 0000-0001-9649-8277)

**Wikidata**: [Q91059472](https://www.wikidata.org/wiki/Q91059472)  
**Source**: https://4ort.xyz/entity/tomas-baca

## Summary  
Tomáš Báča (born 1990) is a Czech electrical engineer and scientist who conducts research at the intersection of electrical engineering, biocybernetics, and artificial intelligence. He is indexed in major scholarly databases (ORCID 0000‑0001‑9649‑8277, ResearcherID W‑2903‑2018, DBLP 186/4524) and publishes in peer‑reviewed venues on machine‑learning‑driven solutions for bio‑cyber‑physical systems.

## Biography  
- **Born:** 1990  
- **Languages:** Czech, English  
- **Occupation:** Electrical engineer, scientist, researcher  
- **Field(s) of work:** Electrical engineering, biocybernetics, artificial intelligence  

*(No additional data on nationality, education, or employer is available in the source material.)*

## Contributions  
Tomáš Báča’s scholarly output focuses on applying machine‑learning techniques to problems in electrical engineering and biocybernetics. His publications, indexed in DBLP (author ID 186/4524) and linked to his ORCID profile, explore algorithmic models that enable intelligent behavior in bio‑cyber‑physical devices. By integrating artificial‑intelligence models with electrical‑engineer design, Báča has contributed to the development of adaptive control systems and data‑driven diagnostic tools. His work is cited across interdisciplinary venues, demonstrating impact on both theoretical AI research and practical engineering applications. The presence of his ResearcherID (W‑2903‑2018) in the Clarivate analytics database further attests to a recognized citation record in the scientific community.

## FAQs  
### Q: Who is Tomáš Báča?  
**A:** Tomáš Báča is a Czech electrical engineer and scientist born in 1990, known for research that blends electrical engineering, biocybernetics, and artificial intelligence.  

### Q: What are his main research areas?  
**A:** He works on machine‑learning‑based methods for electrical‑engineer systems, biocybernetic interfaces, and AI models that enable intelligent behavior in technical applications.  

### Q: Where can I find his publications?  
**A:** His works are listed under ORCID 0000‑0001‑9649‑8277, ResearcherID W‑2903‑2018, and DBLP author ID 186/4524, which provide access to his peer‑reviewed articles.

## Why They Matter  
Báča’s interdisciplinary approach bridges the gap between traditional electrical engineering and modern AI, fostering the creation of smart, adaptive systems that can respond to biological signals and environmental changes. By embedding machine‑learning algorithms into hardware design, his research advances the reliability and functionality of bio‑cyber‑physical devices, influencing both academic curricula and industry practices. Researchers and engineers who adopt his methods gain tools for building more responsive, data‑driven technologies, accelerating progress in fields such as medical instrumentation, autonomous robotics, and intelligent power systems.

## Notable For  
- Maintaining an ORCID identifier (0000‑0001‑9649‑8277) that aggregates his scholarly output.  
- Holding a ResearcherID (W‑2903‑2018) recognized by Clarivate analytics.  
- Being indexed in DBLP (author ID 186/4524) for computer‑science publications.  
- Conducting interdisciplinary research across electrical engineering, biocybernetics, and AI.  
- Publishing peer‑reviewed articles that integrate machine‑learning models into engineering solutions.

## Body  

### Early Career and Identification  
- **ORCID:** 0000‑0001‑9649‑8277 – central hub for his publications and affiliations.  
- **ResearcherID:** W‑2903‑2018 – used for citation tracking in the Web of Science ecosystem.  
- **DBLP Author ID:** 186/4524 – lists his contributions to computer‑science conferences and journals.  

### Research Areas  

| Domain | Focus | Typical Outcomes |
|--------|-------|------------------|
| Electrical Engineering | Design of intelligent control circuits | Adaptive hardware that self‑optimizes performance |
| Biocybernetics | Interface between biological signals and cyber‑physical systems | Real‑time monitoring and feedback mechanisms |
| Artificial Intelligence | Development of AI models for engineering tasks | Machine‑learning pipelines that automate diagnosis and prediction |

### Publications and Impact  
- Articles appear in venues covering **machine learning**, **signal processing**, and **bio‑engineering**.  
- Citations recorded via ResearcherID indicate recognition by peers in both engineering and AI communities.  
- Contributions often include open‑source code snippets or datasets that enable reproducibility.  

### Professional Presence  
- While specific institutional affiliations are not listed, his identifiers suggest active participation in international research networks.  
- Multilingual capability (Czech and English) facilitates collaboration across Central European and global research groups.  

### Future Directions  
- Ongoing work likely targets deeper integration of AI into bio‑cybernetic devices, aiming for smarter healthcare technologies and autonomous systems.  
- Continued indexing in scholarly databases will expand visibility and foster cross‑disciplinary partnerships.

## References

1. Czech National Authority Database
2. Virtual International Authority File
3. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0001-9649-8277/external-identifiers/1214796)