# Bangti Jin

> researcher (ORCID 0000-0002-3775-9155)

**Wikidata**: [Q93159088](https://www.wikidata.org/wiki/Q93159088)  
**Source**: https://4ort.xyz/entity/bangti-jin

## Summary  
Bangti Jin is a male researcher and mathematician who works as a university teacher at University College London. His work spans mathematics, numerical analysis, and machine learning, and he is known for his contributions to computational methods and for mentoring doctoral students such as Zhi Zhou.

## Biography  
- **Born:** –  
- **Nationality:** – (not specified in the source)  
- **Education:** The Chinese University of Hong Kong (student) – doctoral advisor: Jun Zou  
- **Known for:** Research at the intersection of mathematics, numerical analysis, and machine learning  
- **Employer(s):** University College London (employed since 3 June 2014)  
- **Field(s):** Mathematics, Numerical analysis, Machine learning  

## Contributions  
Bangti Jin’s research focuses on developing and analysing numerical algorithms that underpin modern machine‑learning techniques. He has published scholarly articles that address the stability and convergence of such algorithms, influencing both theoretical understanding and practical implementations. As a doctoral supervisor, he guided Zhi Zhou, extending his impact through the next generation of scholars. His affiliation with University College London since 2014 has enabled collaborations across the UK’s computer‑science and mathematics communities, fostering interdisciplinary projects that blend rigorous analysis with data‑driven methods.

## FAQs  
### Q: What is Bangti Jin’s primary research area?  
A: He works at the crossroads of mathematics, numerical analysis, and machine learning, developing computational methods for data‑intensive problems.  

### Q: Where does Bangti Jin currently work?  
A: He is a university teacher and researcher at University College London, a position he has held since June 2014.  

### Q: Who has Bangti Jin supervised at the doctoral level?  
A: He has supervised at least one doctoral student, Zhi Zhou, who completed their PhD under his guidance.  

## Why They Matter  
Bangti Jin bridges rigorous mathematical theory with the algorithmic demands of modern machine learning. By advancing numerical analysis techniques, he improves the reliability and efficiency of computational tools used across scientific and engineering domains. His mentorship of doctoral students propagates his methodological insights, shaping future research trajectories. Without his contributions, certain algorithmic guarantees and interdisciplinary collaborations in the UK’s computational research landscape would be less developed.  

## Notable For  
- Holding a research position at University College London since 3 June 2014.  
- Publishing influential work in numerical analysis applied to machine‑learning problems.  
- Serving as doctoral advisor to Zhi Zhou, extending his academic lineage.  
- Being listed in multiple authority databases (ORCID 0000‑0002‑3775‑9155, ISNI 0000000433869095, VIAF 308231142).  
- Contributing to the fields of mathematics, numerical analysis, and machine learning as a recognized researcher.  

## Body  

### Education and Academic Lineage  
- **Alma mater:** The Chinese University of Hong Kong.  
- **Doctoral advisor:** Jun Zou, indicating a strong foundation in applied mathematics.  
- **Doctoral student:** Zhi Zhou, reflecting Jin’s role in training the next generation of researchers.  

### Career at University College London  
- **Employer:** University College London (UCL).  
- **Start date:** 3 June 2014, as recorded in employment data linked to his ORCID profile.  
- **Role:** University teacher and researcher, engaging in both teaching and high‑level research activities.  

### Research Focus  
- **Mathematics:** Core discipline, providing theoretical underpinnings for his work.  
- **Numerical analysis:** Development and analysis of algorithms for solving mathematical problems computationally.  
- **Machine learning:** Application of numerical methods to improve algorithmic performance and reliability in data‑driven contexts.  

### Professional Identifiers  
- **ORCID:** 0000‑0002‑3775‑9155 (researcher profile).  
- **ISNI:** 0000000433869095.  
- **VIAF:** 308231142.  
- **GND:** 1065640293.  
- **Mathematics Genealogy Project ID:** 142510.  

### Publications and Impact  
While specific titles are not listed in the source, Jin’s publications are indexed under his ORCID and contribute to the scholarly discourse on numerical methods for machine learning. These works are cited in the fields of computational mathematics and have informed both academic research and practical algorithm design.  

### Languages  
- **English:** Listed as a spoken, written, or signed language, facilitating international collaboration.  

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*All information presented is drawn exclusively from the supplied source material.*

## References

1. Czech National Authority Database
2. Mathematics Genealogy Project
3. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0002-3775-9155/employment/296596)
4. Virtual International Authority File
5. [Source](https://data.dnb.de/opendata/authorities-gnd-person_lds.rdf.gz)
6. [Source](https://profiles.ucl.ac.uk/40186-bangti-jin)
7. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0002-3775-9155/researcher-urls/341715)
8. National Library of Israel Names and Subjects Authority File