# Paolo Ferragina

> Italian professor of algorithms

**Wikidata**: [Q109778059](https://www.wikidata.org/wiki/Q109778059)  
**Source**: https://4ort.xyz/entity/paolo-ferragina

## Summary
Paolo Ferragina is an Italian computer scientist and professor specializing in algorithms. He is known for his significant contributions to compressed data structures and received the prestigious Paris Kanellakis Award in 2022 for his work in theoretical computer science.

## Biography
- Born: June 27, 1969, in Catanzaro, Italy
- Nationality: Italy
- Education: PhD in Computer Science from University of Pisa (1996), also educated at Max Planck Institute for Informatics
- Known for: Research in algorithms and compressed data structures
- Employer(s): University of Pisa, Sant'Anna School of Advanced Studies
- Field(s): Computer science, algorithms, data compression

## Contributions
Paolo Ferragina has made significant contributions to the field of algorithms, particularly in the area of compressed data structures. His research focuses on developing efficient algorithms for processing compressed data, which has important implications for data storage and retrieval systems. As a full professor, he has supervised numerous doctoral students including Francesco Tosoni, Andrea Guerra, and others, contributing to the next generation of computer scientists. His work bridges theoretical computer science with practical applications in data compression and information retrieval.

## FAQs
### Q: What awards has Paolo Ferragina received?
A: Paolo Ferragina received the Paris Kanellakis Award in 2022 and was named an ACM Fellow in 2025 for his contributions to theoretical computer science.

### Q: Where does Paolo Ferragina work?
A: Paolo Ferragina is affiliated with both the University of Pisa and the Sant'Anna School of Advanced Studies as a professor of algorithms.

### Q: What is Paolo Ferragina's area of expertise?
A: Ferragina specializes in algorithms and compressed data structures, with research focusing on efficient data processing and compression techniques.

### Q: Who has Paolo Ferragina mentored in his academic career?
A: He has supervised numerous doctoral students including Francesco Tosoni, Andrea Guerra, Rossano Venturini, Giorgio Vinciguerra, and others, contributing to their research in algorithms and data structures.

## Why They Matter
Paolo Ferragina's work has significantly advanced the field of algorithms, particularly in compressed data structures. His research has provided theoretical foundations and practical solutions for efficiently processing compressed data, which has implications for data storage, retrieval, and transmission. As an educator, he has mentored numerous doctoral students who have gone on to contribute to the field. His receipt of the Paris Kanellakis Award and ACM Fellowship recognition underscores the impact and quality of his contributions to computer science. Without his work, the development of efficient algorithms for compressed data processing would have been significantly delayed.

## Notable For
- Received the Paris Kanellakis Award in 2022 for contributions to theoretical computer science
- Named ACM Fellow in 2025 for excellence and impact in computing
- Serves as a full professor at both University of Pisa and Sant'Anna School of Advanced Studies
- Supervised numerous doctoral students who have made significant contributions to algorithms and data structures
- Has developed research in compressed data structures that bridges theoretical computer science with practical applications

## Body
### Academic Background
Paolo Ferragina was born on June 27, 1969, in Catanzaro, Italy. He obtained his PhD in Computer Science from the University of Pisa in 1996 and also received education at the Max Planck Institute for Informatics. His academic journey has established him as a prominent figure in the field of computer science.

### Professional Career
Ferragina currently holds the position of full professor at both the University of Pisa and the Sant'Anna School of Advanced Studies. His research focuses on algorithms and compressed data structures, with applications in data compression and information retrieval. He has maintained an active research program, publishing numerous papers and contributing to the advancement of theoretical computer science.

### Research Contributions
Ferragina's research centers on developing efficient algorithms for processing compressed data. His work has important implications for how data is stored, retrieved, and transmitted in modern computing systems. He has explored various aspects of data compression and developed novel approaches to handling compressed information efficiently.

### Mentoring and Academic Influence
As an educator, Ferragina has supervised numerous doctoral students, including Francesco Tosoni, Andrea Guerra, Rossano Venturini, Giorgio Vinciguerra, Igor Nitto, Marco Ponza, Antonio Boffa, Francesco Piccinno, and Marco Cornolti. His mentorship has helped shape the next generation of computer scientists working in algorithms and data structures.

### Recognition and Awards
Ferragina's contributions to computer science have been recognized with several prestigious awards. He received the Paris Kanellakis Award in 2022 and was named an ACM Fellow in 2025. These honors acknowledge his significant impact on theoretical computer science and his excellence in the field.

## References

1. BnF authorities
2. [Source](https://www.santannapisa.it/it/paolo-ferragina)
3. [Source](https://awards.acm.org/kanellakis/award-recipients)
4. [Excellence and Impact Recognized by World’s Preeminent Computing Society. 2026](https://awards.acm.org/binaries/content/assets/press-releases/2026/january/2025-acm-fellows-press-release.pdf)
5. [Computation-friendly compression of matrices and tries. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-04182024-175520)
6. [Compressing and Efficient Query Processing for Large-Scala Data Sequences. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-11212025-095528)
7. [On searching and extracting strings from compressed textual data. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-05192010-120514)
8. [On Two Web IR Boosting Tools: Clustering and Ranking. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-12222005-090239)
9. [Learning-based compressed data structures. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-01292022-141555)
10. [Parsing Algorithms for Data Compression. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-05252010-115131)
11. [Algorithms for Knowledge and Information Extraction in Text with Wikipedia. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-02192019-141256)
12. [Designing new compressed data structures using data-aware approaches. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-04192024-113322)
13. [Algorithms and data structures for big labeled graphs. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-03242017-172141)
14. [Entity Linking on Text and Queries. Sistema bibliotecario di ateneo, Università di Pisa](https://etd.adm.unipi.it/t/etd-03242017-173633)
15. [Building a Biomedical Knowledge Graph from PubMed Central articles. Sistema bibliotecario di ateneo, Università di Pisa](https://dx.doi.org/10.25429/bellomo-lorenzo_phd2024-04-22)
16. [Source](https://viaf.org/viaf/data/viaf-20230206-links.txt.gz)
17. Virtual International Authority File
18. [Source](https://aleph.nkp.cz/F/?func=find-c&local_base=aut&ccl_term=ica=stk2007383259&CON_LNG=ENG)
19. [Paolo Ferragina](https://gutenbergcalabria.it/aut/paolo-ferragina/)