Daniel Lemire

Daniel Lemire

Title :Computer Scientist and Professor - Université du Québec

Bio: 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 eBay, LinkedIn, Facebook and Netflix in their data warehousing, within big-data platforms such as Apache Hive, Druid, Apache Spark, Netflix Atlas, LinkedIn Pinot 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. One of his hashing techniques has been adopted by Google TensorFlow. His Slope One recommender algorithm is a standard reference in the field of recommender systems. He is a beneficiary of the Google Open Source Peer Bonus Program. He has written over 50 peer-reviewed publications, including more than 30 journal articles. He has held competitive research grants for the last 15 years. He serves on the program committees of leading computer science conferences (e.g., ACM CIKM, WWW, ACM WSDM, ACM SIGIR, ACM RecSys).

Maps and Sets can have Quadratic-time Performance

Maps and Sets can have Quadratic-time Performance

Swift is a new programming language launched by Apple slightly over two years ago. Like C and C++, it offers ahead-of-time compilation to native code but with many new modern features. It is available on Linux and macOS. Like C++, Swift comes complete with its own data structures like dictionaries (key-value or associative maps) and […]

Deep Learning: the Silver bullet?

Deep Learning: the Silver bullet?

In 2016, we saw a wide range of breakthroughs having to do with artificial intelligence and deep learning in particular. Google, Facebook, and Baidu announced several breakthroughs using deep learning. Google also defeated Go. Deep learning is one specific class of machine learning algorithms. It has a long history, taking its roots in the earlier […]

Quick Alternative to Modulo Reduction

Quick Alternative to Modulo Reduction

Suppose you want to pick an integer at random in a set of N elements. Your computer has functions to generate random 32-bit integers, how do you transform such numbers into indexes no larger than N? Suppose you have a hash table with a capacity N. Again, you need to transform your hash values (typically 32-bit […]