Daniel Lemire

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Data Science, Indexing and Software Performance.

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Daniel Lemire is a full professor in computer science at the University of Quebec (TELUQ). His research is focused on data indexing techniques. For example, he worked on bitmap indexes, column-oriented databases and integer compression. He is also interested in database design and probabilistic algorithms (e.g., universal hashing). His work on bitmap indexes is used by companies such as Facebook and Netflix in their datawarehousing, within big-data platforms such as Apache Hive, Druid, Apache Spark and Apache Kylin. The version control system Git is also accelerated by the same compressed bitmaps. Some of his techniques were adopted by Apache Lucene, the search engine behind sites such as Wikipedia or platforms such as Solr and Elastic. His Slope One recommender algorithm is a standard reference in the field of recommender systems. He has written over 45 peer-reviewed publications, including more than 25 journal articles. He has held competitive research grants for the last 15 years. He has been an expert on several committees with funding agencies (NSERC and FQRNT). He has served as program committee member on leading computer science conferences (e.g., ACM CIKM, ACM WSDM, ACM SIGIR, ACM RecSys).


Daniel Lemire, professor LICEF Research Center, TELUQ Université du Québec 5800 Saint-Denis Office 1105 Montreal (Quebec) H2S 3L5 Canada
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Room 12.166, Email : lemire (at) gmail (dot) com

When visiting, come by the eleventh floor, take the stairs and find my office on the twelfth floor near the LICEF Research Center.

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© 2001-2016, Daniel Lemire (lemire at gmail dot com)