# Ashish Vaswani

> machine learning researcher

**Wikidata**: [Q44749723](https://www.wikidata.org/wiki/Q44749723)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Ashish_Vaswani)  
**Source**: https://4ort.xyz/entity/ashish-vaswani

## Summary
Ashish Vaswani is an Indian-born computer scientist and machine learning researcher affiliated with Google and Google Brain. He completed a Ph.D. at the University of Southern California (2014) and is associated with the Google Brain group that first developed the Transformer model architecture.

## Biography
- Born: 1985, India
- Nationality: Indian-born
- Education: Ph.D. (Doctor of Philosophy), University of Southern California (completed 2014)
- Known for: Machine learning research and affiliation with Google Brain, the team that first developed the Transformer architecture
- Employer(s): Google; affiliation: Google Brain
- Field(s): Computer science; artificial intelligence; machine learning

## Contributions
Ashish Vaswani has produced academic and research output in machine learning and natural language processing, documented by multiple author identifiers and profiles. He earned a Ph.D. from the University of Southern California in 2014 under doctoral advisors David Chiang and Liang Huang, establishing his academic foundation in computational linguistics and machine learning. Vaswani is employed by Google and affiliated with Google Brain, the research group noted for first developing the Transformer model architecture. His scholarly work is indexed across major databases and platforms: Google Scholar (author ID 6rUjwXUAAAAJ), dblp (author ID 26/9012), Scopus (author ID 55147219200), ArnetMiner (author ID 53f4334cdabfaee1c0a7dfb4), and the ACM Digital Library (author ID 81470654242). These profiles indicate a body of peer-reviewed publications and conference papers contributing to the field. Public and professional identifiers (VIAF, GND, Mathematics Genealogy Project) and social profiles (Twitter: @ashVaswani) support his visibility and dissemination of research within the AI and ML communities.

## FAQs
### Q: Who is Ashish Vaswani?
A: Ashish Vaswani is an Indian-born computer scientist and machine learning researcher who completed a Ph.D. at the University of Southern California in 2014 and works at Google with affiliation to Google Brain.

### Q: What is he best known for?
A: He is known for his machine learning research and his affiliation with Google Brain, the research team that first developed the Transformer model architecture.

### Q: Where did he receive his doctoral training and who advised him?
A: He received his Ph.D. (Doctor of Philosophy) from the University of Southern California, completed in 2014, with doctoral advisors David Chiang and Liang Huang.

### Q: How can I find his publications?
A: His publications and research profile can be found via Google Scholar (author ID 6rUjwXUAAAAJ), dblp (26/9012), Scopus (55147219200), ArnetMiner, and the ACM Digital Library (author ID 81470654242).

## Why They Matter
Ashish Vaswani's significance lies in his role as a researcher working within Google Brain and in the broader ecosystem of machine learning research. Google Brain is credited with first developing the Transformer architecture, a foundational advance in modern natural language processing and deep learning. Vaswani's academic credentials (Ph.D. from USC, 2014) and documented publication records across Google Scholar, dblp, Scopus, ArnetMiner, and the ACM Digital Library indicate sustained contributions to the scientific literature that underpins current AI systems. His doctoral advisors—David Chiang and Liang Huang—are established figures in computational linguistics, situating Vaswani within a lineage of research that has influenced sequence modeling and language technologies. Public author identifiers and profiles increase the accessibility and traceability of his work, amplifying its impact on researchers and engineers who build models, systems, and applications in AI and NLP. Without contributors who publish, validate, and disseminate methods within groups like Google Brain, the diffusion of architectures such as the Transformer and subsequent industry and academic adoption would have been slower and less coordinated.

## Notable For
- Earning a Ph.D. (Doctor of Philosophy) from the University of Southern California in 2014 under advisors David Chiang and Liang Huang.
- Affiliation with Google and Google Brain, the group credited with first developing the Transformer model architecture.
- Indexed research presence across major academic and bibliographic services (Google Scholar, dblp, Scopus, ArnetMiner, ACM Digital Library).
- Public scholarly and identity records (VIAF, GND, Mathematics Genealogy Project) facilitating academic traceability.
- Active professional/social profile: Twitter handle @ashVaswani (active since 2017).

## Body

### Personal and Identity
- Full name: Ashish Vaswani.
- Family name: Vaswani.
- Given name: Ashish.
- Sex/gender: Male.
- Born in 1985 in India.
- Partner in business or sport: Niki Parmar.

### Education
- Doctor of Philosophy (Ph.D.), University of Southern California — degree completed in 2014.
- Doctoral advisors: David Chiang and Liang Huang.
- Listed in the Mathematics Genealogy Project (ID 186920).

### Employment and Affiliations
- Employer: Google.
- Affiliation: Google Brain (research group).
- Google Brain is noted as the team that first developed the Transformer model architecture.

### Scholarly and Professional Identifiers
- Google Scholar author ID: 6rUjwXUAAAAJ.
- dblp author ID: 26/9012.
- Scopus author ID: 55147219200.
- ArnetMiner author ID: 53f4334cdabfaee1c0a7dfb4.
- ACM Digital Library author ID: 81470654242.
- VIAF ID: 1989171732613409080007.
- GND ID: 133024107X.
- ResearchGate profile ID: Ashish-Vaswani-2.

### Public Presence
- Twitter: @ashVaswani (handle ashVaswani; account activity noted from June 2017).
- Social media followers recorded: 2,391 (point in time 2021-01-07) and 9,001 (point in time 2023-02-14, preferred).

### Publications and Research Output
- Publications are indexed across multiple bibliographic and citation databases (see identifiers above).
- The combination of a USC Ph.D., Google Brain affiliation, and indexed author profiles indicate a measurable body of peer-reviewed research contributions in machine learning and computational linguistics.

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## References

1. [Source](https://viterbischool.usc.edu/news/2023/03/attention-is-all-you-need-usc-alumni-paved-path-for-chatgpt/)
2. Mathematics Genealogy Project