World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
13852
World Ranking
12350
National Ranking
786

Overview

Victor Lavrenko is affiliated with the University of Edinburgh in the United Kingdom. Their research primarily focuses on medicine, with a particular emphasis on infectious diseases, epidemiology, and statistical and nonlinear physics. Their work also touches on related fields such as sociology and political science, and neurology.

Their recent scholarly contributions include a variety of papers published in notable venues. These papers are:

  • RT to Win! Predicting Message Propagation in Twitter, 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • Morbidity of SARS-CoV-2 in the evolution to endemicity and in comparison with influenza, 2024, Communications Medicine
  • Comparative Organ Disease Burden and Sequelae of Influenza and SARS-CoV-2 Infection: An Observational Study Using Real-World Data, 2023, bioRxiv (Cold Spring Harbor Laboratory)
  • Author Correction: Morbidity of SARS-CoV-2 in the evolution to endemicity and in comparison with influenza, 2025, Communications Medicine

The main topics addressed in their research include misinformation and its impacts, complex network analysis techniques, opinion dynamics and social influence, as well as SARS-CoV-2 detection and testing. Their studies also cover SARS-CoV-2 and COVID-19 research and respiratory viral infections, along with influenza virus research studies.

Victor Lavrenko has collaborated frequently with a number of co-authors, including István Bartha, M. Cyrus Maher, Keith Boundy, Elizabeth Kinter, and Wendy W. Yeh. Each of these collaborators has partnered on multiple occasions, contributing to several key publications.

Their publications appear often in the journal Communications Medicine, as well as the Proceedings of the International AAAI Conference on Web and Social Media and bioRxiv (Cold Spring Harbor Laboratory).

Best Publications

  • Relevance-Based Language Models

    Victor Lavrenko;W. Bruce Croft

  • Automatic image annotation and retrieval using cross-media relevance models

    J. Jeon;V. Lavrenko;R. Manmatha

  • Multiple Bernoulli relevance models for image and video annotation

    S.L. Feng;R. Manmatha;V. Lavrenko

  • On-line new event detection and tracking

    James Allan;Ron Papka;Victor Lavrenko

  • A Model for Learning the Semantics of Pictures

    Victor Lavrenko;R. Manmatha;Jiwoon Jeon

  • Streaming First Story Detection with application to Twitter

    Saša Petrović;Miles Osborne;Victor Lavrenko

  • On-line new event detection and tracking

    Unknown

  • RT to Win! Predicting Message Propagation in Twitter

    Sasa Petrovic;Miles Osborne;Victor Lavrenko

  • Holistic word recognition for handwritten historical documents

    V. Lavrenko;T.M. Rath;R. Manmatha

  • Mining of Concurrent Text and Time Series

    Victor Lavrenko;Matt Schmill;Dawn Lawrie;Paul Ogilvie

  • Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002

    James Allan;Jay Aslam;Nicholas Belkin;Chris Buckley

  • Cross-lingual relevance models

    Victor Lavrenko;Martin Choquette;W. Bruce Croft

  • First story detection in TDT is hard

    James Allan;Victor Lavrenko;Hubert Jin

  • Language models for financial news recommendation

    Victor Lavrenko;Matt Schmill;Dawn Lawrie;Paul Ogilvie

  • The Edinburgh Twitter Corpus

    Saša Petrović;Miles Osborne;Victor Lavrenko

  • Profiling of Short-Tandem-Repeat Disease Alleles in 12,632 Human Whole Genomes

    Haibao Tang;Ewen F. Kirkness;Christoph Lippert;William H. Biggs

  • A Generative Theory of Relevance

    Victor Lavrenko

  • Relevance Feedback and Personalization: A Language Modeling Perspective.

    W. Bruce Croft;Stephen Cronen-Townsend;Victor Lavrenko

  • A search engine for historical manuscript images

    Toni M. Rath;R. Manmatha;Victor Lavrenko

  • Identification of individuals by trait prediction using whole-genome sequencing data

    Christoph Lippert;Riccardo Sabatini;M. Cyrus Maher;Eun Yong Kang

  • Relevance models for topic detection and tracking

    Victor Lavrenko;James Allan;Edward DeGuzman;Daniel LaFlamme

  • Sentiment Retrieval using Generative Models

    Koji Eguchi;Victor Lavrenko

Frequent Co-Authors

James Allan
James Allan University of Massachusetts Amherst
Miles Osborne
Miles Osborne Bloomberg LP
R. Manmatha
R. Manmatha Amazon (United States)
Amalio Telenti
Amalio Telenti VIR Biotechnology (United States)
W. Bruce Croft
W. Bruce Croft University of Massachusetts Amherst
Franz Josef Och
Franz Josef Och Google (United States)
Haibao Tang
Haibao Tang Fujian Agriculture and Forestry University
C. Thomas Caskey
C. Thomas Caskey Baylor College of Medicine
J. Craig Venter
J. Craig Venter J. Craig Venter Institute
Bing Ren
Bing Ren New York Genome Center

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Pursuing Computer Science in the USA opens doors to a wide spectrum of related online degrees and lucrative career paths. For those interested in intersecting fields, online electrical engineering programs offer a flexible way to gain in-demand tech skills and provide impressive online electrical engineering career outcomes such as high salaries and diverse job prospects.

Not every path requires years of study. Students wanting quick entry into the tech workforce can explore short certificate programs that pay well. These certifications, many of which are available online, help you develop specialized skills and can fast-track your career.

For those seeking advanced credentials without a long commitment, consider the shortest online masters degree programs. These options let busy professionals upskill and gain a competitive edge efficiently.

If your goal is long-term employability, look into which master's degree is most in demand in usa. Degrees in areas like data science, artificial intelligence, and cybersecurity are especially valuable and align closely with current and future tech job markets.

Best Scientists Citing Victor Lavrenko

Trending Scientists

Recently Published Articles