George Karypis

Professor, Department of Computer Science & Engineering

Distinguished McKnight University Professor, Department of Computer Science & Engineering

Contact

karypis@umn.edu

612-626-7524

483 Walter Library
117 Pleasant St. SE
Minneapolis, MN 55455

George Karypis

Professor, Department of Computer Science & Engineering

Distinguished McKnight University Professor, Department of Computer Science & Engineering

Research

Karypis' research interests are concentrated in the areas of data mining, recommender systems, learning analytics, high-performance computing, and chemical informatics and from time-to-time, he looks at various problems in the areas of health informatics, information retrieval, bioinformatics, and scientific computing. Within these areas, his research focuses in developing novel algorithms for solving important existing and/or emerging problems, and on developing practical software tools implementing some of these algorithms. The results from this research have been presented in various conferences and published in leading peer reviewed journals and highly selective conference proceedings.

Research Division
Data Science and Machine Learning

Current Research
Google Scholar
Bioinformatics
Chemical Informatics
Data Mining
Discovery of Patterns in the Global Climate System using Data Mining

Karypis Lab

Ph.D. Graduates
Shalini Pandey (2021); Saurav Manchanda (2020); Agoritsa Polyzou (2020); Sara Morsy (2019); Shaden Smith (2019); Evangelia Christakopoulou (2018); Jeremy Iverson (2017); Mohit Sharma (2017); Asmaa El Badrawy (2017); David Anastasiu (2016); Dominique LaSalle (2015); Santosh Kabbur (2015); Rezwan Ahmed (2014); Chris Kauffman (2013); Zhonghua Jiang (2013); Kevin DeRonne (2013); Xia Ning (2012); Nikil Wale (2008); Huzefa Rangwala (2008); Irina Makarevitch (2005); Ying Zhao (2005; co-advised with David Du); Michihiro Kuramochi (2005); Irene Moulitsas (2005; co-advised with Yousef Saad); Navaratnasothie Selvakumaran (2005); Mukund Deshpande (2003; co-advised with Jaideep Srivastava); William Leinberger (2001; co-advised with Vipin Kumar); Valery Guralnik (2001; with Jaideep Srivastava); Kirk Schloegel (1999; co-advised with Vipin Kumar).

Recent News

CS&E makes big showing at IEEE BigData 2021
Karypis and Kumar receive Test of Time award at SC21
CS&E faculty ranked among top CS researchers in the world
Karypis wins PAKDD Distinguished Contributions Award
CS&E wins prestigious 10-Year Highest-Impact award at ICDM
Professor Karypis receives COGS Outstanding Advisor Award
Fighting COVID-19 with deep graphs

Visit George Karypis's Experts@Minnesota profile page

Biography

Education

Ph.D. in Computer Science, University of Minnesota (1996)
B.S. in Computer Science, University of Minnesota (1992)

Professional Background

George Karypis joined the Department of Computer Science & Engineering in 1999. He was promoted to full professor in 2009. He is the co-author of two books and has contributed to the development of multiple software libraries. Additionally, he serves on the program committees of many conferences and workshops, and on the editorial boards of the IEEE Transactions on Big Data, ACM Transactions on Knowledge Discovery from Data, Data Mining and Knowledge Discovery, Journal of Data Science and Analytics, Social Network Analysis and Data Mining Journal, International Journal of Data Mining and Bioinformatics, the journal on Current Proteomics, Advances in Bioinformatics, and Biomedicine and Biotechnology. He is an IEEE Fellow.

Visit George Karypis's Experts@Minnesota profile page.

Recent News

Teaching

Publications & Awards

Honors and Awards

2021: PAKDD Distinguished Contributions Award
2019: Council of Graduate Students (COGS) Outstanding Advisor Award
2017: IEEE Fellow
2016: McKnight Professorships
2002: National Science Foundation Faculty Early Career Development Program (CAREER Award)

Selected Grants
Collaborative Research: Reliable Materials Simulation based on the Knowledgebase of Interatomic Models (KIM)
Tadmor, E. B., Elliott, R. S. & Karypis, G.; National Science Foundation; 10/1/18 - 9/30/23

High-Performance Static and Streaming Tensor Factorization Algorithms
Karypis, G.; US DEPT OF DEFENSE ARMY; 8/10/18 → 8/9/22

III: Medium: High-Performance Factorization Tools for Constrained and Hidden Tensor Models
Karypis, G. & Sidiropoulos, N.; National Science Foundation; 9/1/17 - 8/31/23

Data Science Research Interests