# Bhargavi Paranjape

> computer scientist

**Wikidata**: [Q128332247](https://www.wikidata.org/wiki/Q128332247)  
**Source**: https://4ort.xyz/entity/bhargavi-paranjape

## Summary
Bhargavi Paranjape is a computer scientist and artificial intelligence researcher affiliated with the University of Washington Paul G. Allen School of Computer Science & Engineering. She earned a Doctor of Philosophy in computer science from the University of Washington in 2024 and works in AI and machine learning research.

## Biography
- Born: [date and place not available]
- Nationality: [not specified in source]
- Education: Doctor of Philosophy, Computer Science, University of Washington (point in time: 2024); doctoral advisors: Luke Zettlemoyer and Hannaneh Hajishirzi
- Known for: Research in artificial intelligence and machine learning; doctoral research completed at the University of Washington (2024)
- Employer(s): University of Washington Paul G. Allen School of Computer Science & Engineering (affiliation)
- Field(s): Artificial intelligence, machine learning, computer science

## Contributions
Bhargavi Paranjape completed a Doctor of Philosophy in computer science at the University of Washington in 2024 under the supervision of Luke Zettlemoyer and Hannaneh Hajishirzi. Her doctoral research constitutes her principal documented scholarly contribution and forms the basis of her contributions to artificial intelligence and machine learning research. She has a Google Scholar author profile (author id hfZRGpgAAAAJ), indicating a set of indexed scholarly publications associated with her research career. Paranjape maintains an online presence for her work through a personal website (https://bhargaviparanjape.github.io/) and a GitHub account (github.com/bhargaviparanjape), which serve as public points of access to her academic profile and technical artifacts. Her institutional affiliation with the Paul G. Allen School situates her within a major academic center for AI research and education. Identifiers such as VIAF (5366173064727026840008) and the Library of Congress authority id (no2024118228, name form: Paranjape, Bhargavi) record her as an established author and researcher in library and bibliographic systems.

## FAQs
### Q: Who is Bhargavi Paranjape?
A: Bhargavi Paranjape is a computer scientist and artificial intelligence researcher affiliated with the University of Washington Paul G. Allen School. She completed a PhD in computer science at the University of Washington in 2024.

### Q: Where did she study and who advised her doctoral work?
A: She earned her Doctor of Philosophy in computer science at the University of Washington (2024). Her doctoral advisors were Luke Zettlemoyer and Hannaneh Hajishirzi.

### Q: How can I find her publications and code?
A: Her scholarly publications are indexed under her Google Scholar author id (hfZRGpgAAAAJ). She also has a personal website (https://bhargaviparanjape.github.io/) and a GitHub account (github.com/bhargaviparanjape) listed in authoritative records.

## Why They Matter
Bhargavi Paranjape’s significance stems from her role as an emerging researcher who completed doctoral training and produced scholarship within a leading computer science department. Earning a Doctor of Philosophy at the University of Washington in 2024 places her in the academic lineage of advisors Luke Zettlemoyer and Hannaneh Hajishirzi, both established researchers; this mentorship links her work to ongoing research programs in natural language processing and AI at a major institution. Her indexed scholarly record (Google Scholar author id hfZRGpgAAAAJ) and institutional affiliation at the Paul G. Allen School position her contributions to influence peers, collaborators, and students in AI and machine learning. Public identifiers (VIAF, Library of Congress authority id) and online presences (personal website and GitHub) enable discovery, citation, and reuse of her work. While specific publications and project titles are not enumerated here, the documented facts indicate that Paranjape contributes to the corpus of AI research, supports scholarly communication, and participates in the infrastructure—academic, bibliographic, and online—that helps the field advance.

## Notable For
- Earning a Doctor of Philosophy in Computer Science from the University of Washington (2024).
- Affiliation with the University of Washington Paul G. Allen School of Computer Science & Engineering.
- Having Luke Zettlemoyer and Hannaneh Hajishirzi as doctoral advisors.
- Public scholarly and technical presence: personal website (https://bhargaviparanjape.github.io/), GitHub username (bhargaviparanjape), Google Scholar author id (hfZRGpgAAAAJ).
- Bibliographic identifiers: VIAF 5366173064727026840008 and Library of Congress authority id no2024118228 (Paranjape, Bhargavi).

## Body
### Academic background
- Degree: Doctor of Philosophy, Computer Science, University of Washington.
- Point in time for degree: 2024.
- Doctoral advisors: Luke Zettlemoyer; Hannaneh Hajishirzi.

### Institutional affiliation
- Affiliated with: University of Washington Paul G. Allen School of Computer Science & Engineering.
- Role: Computer scientist and artificial intelligence researcher (occupation as recorded).

### Research focus
- Field of work: Artificial intelligence.
- Related areas indicated: Machine learning and computer science generally.

### Scholarly record and identifiers
- Google Scholar author id: hfZRGpgAAAAJ (scholarly publications indexed under this id).
- VIAF identifier: 5366173064727026840008.
- Library of Congress authority id: no2024118228 (authorized name form: Paranjape, Bhargavi).
- Wikidata description: computer scientist.

### Online and professional profiles
- Personal website: https://bhargaviparanjape.github.io/ (English).
- GitHub username: bhargaviparanjape (profile: https://github.com/bhargaviparanjape).
- LinkedIn profile id: bhargaviparanjape (https://www.linkedin.com/in/bhargaviparanjape).

### Cataloging and metadata
- Instance of: human.
- On focus list: WikiProject PCC Wikidata Pilot/University of Washington.

## Schema Markup
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## References

1. WorldCat
2. Virtual International Authority File
3. Library of Congress Name Authority File