PeopleofSuperintelligence

Researcher

Gonzalo Navarro

Gonzalo Navarro is a computer scientist whose compressed data methods support text search, graph queries and matrix operations on machine-learning data. He worked on OCR, graphical interfaces, multimedia and databases at IBM Argentina, then moved to Chile for graduate study at the University of Chile. He coauthored Flexible Pattern Matching in Strings and wrote Compact Data Structures; his later papers cover MillenniumDB, compressed matrices and CompactLTJ. He became an ACM Fellow in 2022 and is a full professor at the University of Chile and an associate researcher at IMFD, where he co-leads the Multimodal Data line with Diego Arroyuelo.

Now at
University of Chile and IMFD
Born
1969
Works
735
Citations
20,971
h-index
68
Badges

Years link to their sources. Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 1991–2000

    From IBM to Chile

    He earns informatics degrees at ESLAI in 1992 and the National University of La Plata in 1993 while working at IBM Argentina's GICAA from 1991 to 1994 on OCR, graphical interfaces, multimedia and databases. He moves to Chile in 1994, earns a master's degree in computer science at the University of Chile in 1995 and a PhD there in 1998, becomes an assistant professor there in 1999, and completes postdoctoral stays at the University of Helsinki and the Institut Gaspard Monge at the University of Marne-la-Vallée in 1999–2000.

  2. 2002–2008

    String matching and promotion

    With Mathieu Raffinot, he coauthors Flexible Pattern Matching in Strings in 2002, a practical guide to string search that covers exact and approximate patterns. At the University of Chile, he becomes an associate professor in 2003 and a full professor in 2008.

  3. 2016

    Compact Data Structures

    In 2016, he publishes Compact Data Structures, a guide to structures that represent data in reduced space while supporting queries, navigation and operations in compressed form.

  4. 2021

    The MillenniumDB graph engine

    In 2021, he coauthors the paper introducing MillenniumDB, a modular, persistent, open-source graph database that supports several graph models. The paper evaluates queries over data and query sets from the Wikidata knowledge graph.

  5. 2022

    Matrices for machine learning

    In 2022, he coauthors a lossless grammar-compression scheme for real-valued matrices that supports matrix-vector multiplication in time and space proportional to the compressed representation. The work addresses how to store and operate on large data collections produced by machine-learning methods.

  6. 2022

    An ACM Fellowship

    In 2022, he is named an ACM Fellow for contributions to text searching and compact data structures.

  7. 2025

    CompactLTJ graph queries

    In 2025, he coauthors CompactLTJ, a space- and time-efficient Leapfrog Triejoin method for graph database queries.

  8. As of October 2026

    Professor and IMFD researcher

    As of October 2026, he is a full professor in the Department of Computer Science at the University of Chile and an associate researcher at IMFD. He co-leads IMFD's Multimodal Data research line with Diego Arroyuelo and teaches the department's Design and Analysis of Algorithms course in 2026.

Career

  1. Since 1999University of ChileAssistant Professor, Associate Professor
  2. NowIMFDAssociate Researcher; Multimodal Data line lead
  3. 2024–2026Fundación Chile
  4. 2015–2026Centre for Biotechnology and Bioengineering
  5. 1999–2000University of HelsinkiPostdoctoral researcher
  6. 1999–2000Université Paris-Est Marne-la-ValléePostdoctoral researcher
  7. 1991–1994IBM Argentina

Education

  1. 1998University of ChilePhD
  2. 1995University of ChileMaster’s degree
  3. 1993National University of La Plata
  4. 1992ESLAI

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  1. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Chile. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Chile. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. 23% of people shaping AI who left a university for a company later returned to a universityIncludes IBM. We estimate that 468 of the 2,011 people shaping AI who left a university for a company (23%) later returned to a university after a median of 5 years, and 163 of 829 (20%) made the reverse round trip.
  4. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes IBM. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Biografía corta users.dcc.uchile.cl. Checked 22 October 2026.
  2. Flexible Pattern Matching in Strings cambridge.org. Checked 22 October 2026.
  3. Compact Data Structures cambridge.org. Checked 22 October 2026.
  4. MillenniumDB: A Persistent, Open-Source, Graph Database arxiv.org. Checked 22 October 2026.
  5. Improving Matrix-vector Multiplication via Lossless Grammar-Compressed Matrices arxiv.org. Checked 22 October 2026.
  6. Gonzalo Navarro distinguido como Fellow de la ACM imfd.cl. Checked 22 October 2026.
  7. Gonzalo Navarro – Instituto Milenio Fundamentos de los Datos imfd.cl. Checked 22 October 2026.
  8. DCC | Académicas/os - Gonzalo Navarro web.dcc.uchile.cl. Checked 22 October 2026.