Professor George Karypis

CSENG Computer Science & Eng
College of Science & Engineering
Twin Cities
Project Title: 
High-Performance and Big Data Research

This group's research spans the fields of high-performance computing, educational data mining, recommender systems, and similarity search.

  • Research in the area of high performance computing focuses on the design and implementation of algorithms for analyzing large scale datasets that arise in machine learning tasks. These tools are used extensively in fields such as anomaly detection, precision healthcare, and recommender systems.
  • Research in the area of educational data mining focuses on the development of predictive models for estimating the performance (i.e., grades) of students on future courses and ranking models for top-N course recommendation. These models aim to help students make informed decisions about which courses to register for, which can improve student retention and lead to successful and timely graduation.
  • Research in the area of recommender systems focuses on the design and development of algorithms to improve the quality of recommendations served to a user of the system. These researchers have developed methods that outperform the current state-of-the-art methods for the top-N recommendation, explicitly modeled the user behavior of providing ratings on sets of items, and investigated the characteristics of large-scale datasets that affect the performance of the existing recommendation methods.
  • Research in the area of similarity search focuses on designing efficient algorithms for discovering similar vectors (called neighbors) within a large set of vectors. These algorithms are essential building blocks in many applications that rely on machine learning.

Project Investigators

Evangelia Christakopoulou
Asmaa Elbadrawy
Professor George Karypis
Sara Morsy
Athanasios Nikolakopoulos
Agoritsa Polyzou
Huzefa Rangwala
Mohit Sharma
Shaden Smith
Ancy Tom
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