# Stefan Haufe

> computer scientist

**Wikidata**: [Q40864048](https://www.wikidata.org/wiki/Q40864048)  
**Source**: https://4ort.xyz/entity/stefan-haufe

## Summary  
Stefan Haufe is a German computer scientist and artificial intelligence researcher known for his work in machine learning and neurotechnology. He is currently an associate professor at Technische Universität Berlin and has held research positions at Columbia University and Charité. His contributions include advancements in interpretable machine learning and brain-computer interfaces.

## Biography  
- Born: No birth date or place available  
- Nationality: German  
- Education: Educated at Technische Universität Berlin  
- Known for: Research in artificial intelligence and machine learning  
- Employer(s): Technische Universität Berlin (current), Charité, Columbia University, City College of New York  
- Field(s): Computer science, artificial intelligence, neurotechnology  

## Contributions  
Stefan Haufe has made significant contributions to machine learning, particularly in interpretable AI and brain-computer interfaces. His research focuses on developing methods to make machine learning models more transparent and applicable to neuroscience. He has collaborated with Klaus-Robert Müller, his doctoral advisor, on projects advancing neurotechnology. Haufe has published extensively, with works indexed in platforms like Scopus, zbMATH, and IEEE Xplore. His Erdős number is 3 (as of 2022), reflecting his collaborative research output.  

## FAQs  
### Q: What is Stefan Haufe's current position?  
A: Stefan Haufe is an associate professor at Technische Universität Berlin, where he leads research in machine learning and neurotechnology.  

### Q: What are Stefan Haufe's primary research interests?  
A: His work focuses on artificial intelligence, interpretable machine learning, and applications in neuroscience, such as brain-computer interfaces.  

### Q: Where did Stefan Haufe complete his education?  
A: He was educated at Technische Universität Berlin, where he also earned his doctorate under the supervision of Klaus-Robert Müller.  

## Why They Matter  
Stefan Haufe's research bridges the gap between theoretical machine learning and practical applications in neuroscience. His work on interpretable AI has influenced how models are designed for transparency, particularly in medical and neurotechnological contexts. Collaborations with institutions like Charité highlight the real-world impact of his research. Without his contributions, advancements in brain-computer interfaces and explainable AI might lag behind current developments.  

## Notable For  
- Associate professor at Technische Universität Berlin  
- Erdős number of 3 (as of 2022)  
- Research collaborations with Klaus-Robert Müller  
- Contributions to interpretable machine learning and neurotechnology  
- Published works indexed in Scopus, zbMATH, and IEEE Xplore  

## Body  
### Education  
- Educated at Technische Universität Berlin  
- Doctoral advisor: Klaus-Robert Müller  

### Career  
- **Columbia University**: Researcher (2014–2016)  
- **City College of New York**: Postdoctoral researcher (2013–2014)  
- **Charité**: Researcher (since 2019)  
- **Technische Universität Berlin**: Associate professor (since 2021)  

### Research  
- Focus areas: Artificial intelligence, interpretable machine learning, neurotechnology  
- Collaborations: Worked with Klaus-Robert Müller on AI and neuroscience projects  
- Publications: Indexed in Scopus (ID: 6701430010), zbMATH, and IEEE Xplore  

### Metrics  
- Erdős number: 3 (as of 2022)  
- Google Scholar ID: fVzmgmYAAAAJ  
- ResearchGate profile: Stefan_Haufe2

## References

1. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1470-9195/employment/4180477)
2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1470-9195/employment/4180478)
3. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-1470-9195/employment/16035146)
4. Open dataset of scholars on Twitter
5. [Source](https://zbmath.org/collaboration-distance/?a=haufe.stefan&b=erdos.paul)
6. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0003-1470-9195/researcher-urls/797617)