Faculty Directory
Diego Klabjan

Professor of Industrial Engineering and Management Sciences

Director of Master of Science in Analytics Program


2145 Sheridan Road
Tech E278
Evanston, IL 60208-3109

Email Diego Klabjan


Master of Science in Analytics

Klabjan's Homepage


Industrial Engineering and Management Sciences


Master of Science in Analytics Program


Ph.D. Industrial Engineering, Georgia Institute of Technology, Atlanta, GA

B.S. Applied Mathematics, University of Ljubljana, Ljubljana, Slovenia


Diego Klabjan is a professor at Northwestern University, Department of Industrial Engineering and Management Sciences. He is also Founding Director, Master of Science in Analytics. After obtaining his doctorate from the School of Industrial and Systems Engineering of the Georgia Institute of Technology in 1999 in Algorithms, Combinatorics, and Optimization, in the same year he joined the University of Illinois at Urbana-Champaign. In 2007 he became an associate professor at Northwestern and in 2012 was promoted to a full professor. His research is focused on machine learning, deep learning and analytics with concentration in finance, transportation, sport, and bioinformatics. Professor Klabjan has led projects with large companies such as Intel, Baxter, Allstate, AbbVie, FedEx Express, General Motors, United Continental, and many others, and is also assisting numerous start-ups with their analytics needs. He is also a founder of Opex Analytics LLC.

Research Interests

Machine learning and artificial intelligence - text analytics, deep learning, optimization; transportation, finance, healthcare

Selected Publications

  • Anders Drachen, James Green, Chester Gray, Elie Harik, Patty Lu, Rafet Sifa, Diego Klabjan, “Guns and guardians”, 2016 IEEE Conference on Computational Intelligence and Games, CIG 2016, (2017)
  • Young Woong Park, Yan Jiang, Diego Klabjan, Loren Williams, “Algorithms for generalized Clusterwise linear regression”, INFORMS Journal on Computing, (2017)
  • Young Woong Park, Diego Klabjan, “Three iteratively reweighted least squares algorithms for L1-norm principal component analysis”, Knowledge and Information Systems, (2017)
  • Alexandros Nathan, Diego Klabjan, “Optimization for large-scale machine learning with distributed features and observations”, Machine Learning and Data Mining in Pattern Recognition - 13th International Conference, MLDM 2017, Proceedings, (2017)
  • Christopher T. Richards, Baiyang Wang, Eddie Markul, Frank Albarran, Doreen Rottman, Neelum T. Aggarwal, Patricia Lindeman, Leslee Stein-Spencer, Joseph M. Weber, Kenneth S. Pearlman, Katie L. Tataris, Jane L. Holl, Diego Klabjan, Shyam Prabhakaran, “Identifying Key Words in 9-1-1 Calls for Stroke”, Prehospital Emergency Care, (2017)
  • Young Woong Park, Diego Klabjan, “Iteratively reweighted least squares algorithms for L1-Norm principal component analysis”, Proceedings - 16th IEEE International Conference on Data Mining, ICDM 2016, (2017)
  • Dong Zhang, Diego Klabjan, “Optimization for gate re-assignment”, Transportation Research, Series B: Methodological, (2017)
  • Timothy M. Sweda, Irina S. Dolinskaya, Diego Klabjan, “Optimal recharging policies for electric vehicles”, Transportation Science, (2017)