# Katrina Ligett

> American computer scientist, California Institute of Technology

**Wikidata**: [Q17517158](https://www.wikidata.org/wiki/Q17517158)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Katrina_Ligett)  
**Source**: https://4ort.xyz/entity/katrina-ligett

## Summary
Katrina Ligett is an American computer scientist known for her work in algorithmic economics and privacy. She is a professor at the Hebrew University of Jerusalem and has held positions at Caltech and Cornell University.

## Biography
- Born: Not specified
- Nationality: United States
- Education: Ph.D. from Carnegie Mellon University; also attended Brown University
- Known for: Research in algorithmic economics, privacy, and machine learning
- Employer(s): Hebrew University of Jerusalem (current), California Institute of Technology (2011-2017), Cornell University (postdoctoral researcher, 2009-2011)
- Field(s): Computer science, algorithmic economics, privacy

## Contributions
Katrina Ligett has made significant contributions to the fields of algorithmic economics and privacy through her research on differential privacy, algorithmic game theory, and machine learning. Her work has focused on developing theoretical foundations for privacy-preserving algorithms and understanding the economic implications of algorithmic decision-making. She has published numerous influential papers on topics such as differential privacy mechanisms, online learning in games, and the intersection of privacy and economics. Her research has helped shape how organizations approach data privacy and has influenced both academic theory and practical applications in tech companies and government agencies.

## FAQs
### Q: What is Katrina Ligett's primary research focus?
A: Katrina Ligett specializes in algorithmic economics and privacy, particularly differential privacy and its applications in machine learning and data analysis.

### Q: Where does Katrina Ligett currently work?
A: She is currently a professor at the Hebrew University of Jerusalem, where she has worked since 2015.

### Q: Who was Katrina Ligett's doctoral advisor?
A: Her doctoral advisor was Avrim Blum at Carnegie Mellon University.

## Why They Matter
Katrina Ligett's work has been foundational in establishing rigorous mathematical frameworks for privacy-preserving computation. Her research on differential privacy has become a standard approach used by major tech companies and government agencies to protect sensitive data while still enabling useful analysis. By bridging computer science, economics, and privacy theory, she has helped create new interdisciplinary approaches to understanding how algorithms affect individual privacy and societal outcomes. Her contributions have influenced both theoretical computer science and practical policy decisions about data protection.

## Notable For
- Developed influential theoretical frameworks for differential privacy
- Published groundbreaking papers on the intersection of privacy and economics
- Mentored notable doctoral students including Rachel Cummings
- Served as a professor at multiple prestigious institutions (Caltech, Hebrew University)
- Contributed to the theoretical foundations of algorithmic game theory

## Body
### Academic Background
Katrina Ligett earned her Ph.D. from Carnegie Mellon University, where she was advised by Avrim Blum. She also attended Brown University as part of her education.

### Career Path
After completing her doctoral studies, Ligett worked as a postdoctoral researcher at Cornell University from 2009 to 2011. She then joined the California Institute of Technology as a faculty member from 2011 to 2017. Since 2015, she has been employed at the Hebrew University of Jerusalem.

### Research Impact
Ligett's research has focused on several key areas: differential privacy (developing mathematical frameworks for protecting individual data), algorithmic economics (studying how algorithms affect economic outcomes), and machine learning theory. Her work has been widely cited and has influenced both academic research and practical applications in tech industry privacy practices.

### Mentorship
She has supervised doctoral students, including Rachel Cummings, who completed her Ph.D. at Caltech in 2017. Her mentorship has helped train the next generation of researchers in privacy and algorithmic economics.

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## References

1. Mathematics Genealogy Project
2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-2780-6656/employment/10954639)
3. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-2780-6656/employment/14392338)
4. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-2780-6656/employment/14392336)
5. Virtual International Authority File
6. [Source](https://data.dnb.de/opendata/authorities-gnd-person_lds.rdf.gz)
7. National Library of Israel