Faculty Directory
Diego Klabjan

Professor of Industrial Engineering and Management Sciences

Director of Master of Science in Analytics Program

Contact

2145 Sheridan Road
Tech E278
Evanston, IL 60208-3109

Email Diego Klabjan

Website

Master of Science in Analytics

Klabjan's Homepage


Departments

Industrial Engineering and Management Sciences

Affiliations

Master of Science in Analytics Program


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Education

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

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


Biography

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, bioinformatics


Selected Publications

  • Xu Teng, Andreas Zfle, Goce Trajcevski, Diego Klabjan, “Location-Awareness in Time Series Compression”, Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings, (2018)
  • Young Woong Park, Diego Klabjan, “Three iteratively reweighted least squares algorithms for L1 -norm principal component analysis”, Knowledge and Information Systems, (2018)
  • Yaxiong Zeng, Diego Klabjan, “Online adaptive machine learning based algorithm for implied volatility surface modeling”, Knowledge-Based Systems, (2018)
  • Rafet Sifa, Eric Pawlakos, Kevin Zhai, Sai Haran, Rohan Jha, Diego Klabjan, Anders Drachen, “Controlling the crucible”, Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2018, (2018)
  • Anders Drachen, Mari Pastor, Aron Liu, Dylan Jack Fontaine, Yuan Chang, Julian Runge, Rafet Sifa, Diego Klabjan, “To be or not to be... social”, Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2018, (2018)
  • Conrado Borraz-Snchez, Diego Klabjan, Molham Aref , “SolverBlox”, Declarative Logic Programming, (2017)
  • Young Woong Park, Diego Klabjan, “Bayesian Network Learning via Topological Order”, Journal of Machine Learning Research, (2017)
  • Christopher Thomas Richards, Baiyang Wang, Eddie Markul, Frank Albarran, Doreen Rottman, Neelum T. Aggarwal, Patricia Lindeman, Leslee Stein-Spencer, Joseph M. Weber, Kenneth Pearlman, Katie L. Tataris, Jane Louise Holl, Diego Klabjan, Shyam Prabhakaran, “Identifying Key Words in 9-1-1 Calls for Stroke”, Prehospital Emergency Care, (2017)