# Thorsten Wuest

> researcher

**Wikidata**: [Q57010036](https://www.wikidata.org/wiki/Q57010036)  
**Source**: https://4ort.xyz/entity/thorsten-wuest

## Summary
Thorsten Wuest is a researcher and management engineer whose work focuses on industrial engineering, Industry 4.0, machine learning, and information management. He has held academic and industry positions including employment at West Virginia University and the Bremer Institut für Produktion und Logistik (Universitat Bremen Bremer Institut für Produktion und Logistik GmbH).

## Biography
- Born: [date and place not provided]
- Nationality: [not provided]
- Education: Doctor of Philosophy, University of Bremen (PhD awarded 2014-11-24); master's degree, University of Bremen (completed 2009); master's degree, Auckland University of Technology (completed 2008); attended University of Southern California (2013–2014)
- Known for: Research and teaching in industrial engineering, Industry 4.0, machine learning, smart technology, Internet of Things, and information management
- Employer(s): West Virginia University (employed July 2015 – July 2021); Universitat Bremen Bremer Institut für Produktion und Logistik GmbH (2009–2015); ThyssenKrupp Industrial Solutions (2008–2009); affiliated with Auckland University of Technology
- Field(s): Industrial engineering; manufacturing technology; product management; Industry 4.0; machine learning; smart technology; Internet of Things; information management; production systems

## Contributions
Thorsten Wuest has produced a body of research and academic work centered on Industry 4.0, production systems, and the application of machine learning and information management to manufacturing and smart technologies. He completed a PhD at the University of Bremen on 2014-11-24 and holds multiple scholarly profiles and identifiers that index his publications, including Google Scholar (author ID BEw2R1MAAAAJ), DBLP (author ID 119/2546), Scopus (author ID 38562618600), ResearcherID A-2245-2014, and other library identifiers (ISNI 0000000500890733; VIAF 314869412; GND 1067597085). His professional timeline documents industry experience at ThyssenKrupp Industrial Solutions (2008–2009), research and development work at the Bremer Institut für Produktion und Logistik (2009–2015), and an academic appointment at West Virginia University (2015–July 2021). These roles facilitated peer-reviewed publications, conference contributions, and supervised academic work in manufacturing technology, IoT, and data-driven production systems (indexed across the above scholarly platforms). Exact titles of individual papers or patents are recorded in those bibliographic profiles.

## FAQs
### Q: What does Thorsten Wuest research?
A: He researches industrial engineering topics, especially Industry 4.0, machine learning applied to production systems, smart technologies, the Internet of Things, and information management.

### Q: Where has Thorsten Wuest worked?
A: His documented employers include ThyssenKrupp Industrial Solutions (2008–2009), the Bremer Institut für Produktion und Logistik (2009–2015), and West Virginia University (July 2015–July 2021). He is also affiliated with Auckland University of Technology.

### Q: What are Thorsten Wuest's academic qualifications?
A: He holds a Doctor of Philosophy from the University of Bremen (PhD awarded 2014-11-24) and completed master’s-level study at Auckland University of Technology (2008) and the University of Bremen (2009). He also attended the University of Southern California in 2013–2014.

## Why They Matter
Thorsten Wuest’s significance lies in bridging academic research and industry practice within manufacturing and production technology. His documented fields of work—Industry 4.0, machine learning, IoT, and information management—are central to modern efforts to digitize and automate production systems. By working in both corporate engineering (ThyssenKrupp Industrial Solutions) and research institutions (Bremer Institut) before holding an academic appointment at West Virginia University, Wuest participated in applied research pipelines that connect laboratory methods and industrial deployment. His PhD and indexed publication records (accessible via Google Scholar, DBLP, Scopus, and other identifiers) provide a persistent scholarly footprint used by other researchers and practitioners to find, cite, and build upon his work. Without contributors who operate across industry and academia in these areas, the practical adoption of data-driven manufacturing and information-management practices would progress more slowly. Wuest’s multilingual background (German and English) and international education and employment further support collaboration across regions where Industry 4.0 and smart manufacturing initiatives are advancing.

## Notable For
- Earning a Doctor of Philosophy from the University of Bremen (PhD awarded 2014-11-24).
- Employment at West Virginia University from July 2015 until July 2021.
- Research and development role at Universitat Bremen Bremer Institut für Produktion und Logistik GmbH (2009–2015).
- Scholarly presence across major bibliographic platforms (Google Scholar ID BEw2R1MAAAAJ; DBLP 119/2546; Scopus 38562618600; ResearcherID A-2245-2014).
- Work spanning Industry 4.0, machine learning, Internet of Things, and information management in production systems.

## Body
### Education
- University of Bremen
  - Completed a master's degree in 2009.
  - Awarded Doctor of Philosophy on 2014-11-24.
- Auckland University of Technology
  - Completed a master's degree in 2008.
- University of Southern California
  - Attended during 2013–2014 (education record).

### Employment history
- ThyssenKrupp Industrial Solutions
  - Employed 2008–2009.
- Universitat Bremen Bremer Institut für Produktion und Logistik GmbH
  - Employed 2009–2015.
  - Headquarters recorded in Bremen, Germany.
- West Virginia University
  - Employed from July 2015 until July 2021.
- Affiliation
  - Listed as affiliated with Auckland University of Technology (institutional link recorded).

### Research areas and activity
- Documented fields of work:
  - Industrial engineering; manufacturing technology; product management.
  - Industry 4.0; machine learning; smart technology; Internet of Things.
  - Information management; production system research.
- Scholarly outputs are indexed under multiple academic identifiers and databases.
- Research profile identifiers:
  - Google Scholar author ID: BEw2R1MAAAAJ.
  - DBLP author ID: 119/2546.
  - Scopus author ID: 38562618600.
  - ResearcherID: A-2245-2014.

### Identifiers and authority records
- ISNI: 0000000500890733.
- VIAF: 314869412.
- GND (DDB person): 1067597085.
- Dimensions author ID: 010725360373.12.
- National Library of Israel ID: 987012501859405171.
- nl_cr_aut_id: ntk20201089233.

### Languages and personal data
- Languages recorded: English and German.
- Sex/gender: male (recorded).

### Notes
- This entry uses only the provided source data. Where specific publication titles, patent numbers, or award names exist, they are recorded in the cited bibliographic and institutional profiles referenced above.

## References

1. Integrated Authority File
2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7457-7927/education/1356248)
3. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7457-7927/education/1356257)
4. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7457-7927/education/1356249)
5. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7457-7927/education/1356253)
6. Czech National Authority Database
7. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7457-7927/employment/1356265)
8. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7457-7927/employment/1356263)
9. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-7457-7927/employment/1356267)
10. [Czech National Authority Database](https://www.nkp.cz/o-knihovne/odborne-cinnosti/otevrena-data)
11. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0001-7457-7927/external-identifiers/66610)
12. National Library of Israel Names and Subjects Authority File