Professor, School of

Computing Science

Associate Member,

Department of Statistics

and Actuarial Science

Fellow of the Royal Society of Canada (FRSC)

Fellow of Canadian Academy of Engineering (CAE)

Fellow of ACM

Fellow of IEEE

Research Areas: data science, big data, data mining, database systems, and enterprise data strategies

About Me

Jian Pei is a Professor in the School of Computing Science at Simon Fraser University, and also an associate member of the Department of Statistics and Actuarial Science. He is a well known leading researcher in the general areas of data science, big data, data mining, and database systems. His expertise is on developing effective and efficient data analysis techniques for novel data intensive applications, and transferring to products and business practice. He is recognized as a Fellow of the Royal Society of Canada (Canada's national academy), a Fellow of the Canadian Academy of Engineering, a Fellow of the Association of Computing Machinery (ACM) and as a Fellow of the Institute of Electrical and Electronics Engineers (IEEE).

Jian Pei is one of the most cited authors in data mining, database systems, and information retrieval. Since 2000, he has published one textbook, two monographs and over 270 research papers in refereed journals and conferences, which have been cited by more than 92,000 in literature. His H-index is 86 according to Google Scholar. His research has generated remarkable impact substantially beyond academia. For example, his algorithms have been adopted by industry in production and popular open source software suites.

Jian Pei’s professional leadership is also demonstrated by his leadership in many academic organizations and activities. He was the editor-in-chief of the IEEE Transactions of Knowledge and Data Engineering (TKDE) in 2013-16, is currently the chair of the Special Interest Group on Knowledge Discovery in Data (SIGKDD) of the Association for Computing Machinery (ACM), and a general co-chair or program committee co-chair of many premier conferences.

He maintains a wide spectrum of industry relations with both global and local industry partners. He is an active consultant and coach for industry on enterprise data strategies, healthcare informatics, network security intelligence, computational finance, and smart retail. His industry partners and customers include Fortune Global 500 companies and unicorn startups. In his recent sabbatical and extended study leave, he held business executive and technical leadership positions for two Fortune Global 500 companies.

He received many prestigious awards, including the 2017 ACM SIGKDD Innovation Award (the highest award for technical excellence in data science), the 2015 ACM SIGKDD Service Award, the 2014 IEEE ICDM Research Contributions Award, the British Columbia Innovation Council 2005 Young Innovator Award, an NSERC 2008 Discovery Accelerator Supplements Award (100 awards cross the whole country), an IBM Faculty Award (2006), a KDD Best Application Paper Award (2008), an ICDE Influential Paper Award (2018), a PAKDD Best Paper Award (2014), a PAKDD Most Influential Paper Award (2009), and an IEEE Outstanding Paper Award (2007).


I am actively recruiting dedicated and smart postdoc fellows and Ph.D. students. Typically, I take only 1-2 new graduate students every year to ensure my close interaction and collaboration with my students. Full financial support is guaranteed for all full time students in my group.

Currently, I am taking students for the following directions.

  • Advanced knowledge acquisition, such as knowledge modules, temporal knowledge, objectives and subjective knowledge, etc.

  • enterprise data and information infrastructure

  • Fraud/intruction detection and investigation

All students are expected to have a strong background on algorithms, data mining, databases, programming, discrete mathematicsp (graph theory, algebra, set theory, logics), probability and statistics.

I do not take students in the professional master's programs at SFU. I also do not take non-SFU students for summer internship. Visiting Ph.D. students may be considered.

If interested, please send an email to <>.