Faculty Directory
Diego Klabjan

Professor of Industrial Engineering and Management Sciences

Director of Master of Science in Analytics Program

Director, Center for Deep Learning

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


Download CV

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

  • Ye Xue, Diego Klabjan, Yuan Luo, “Predicting ICU readmission using grouped physiological and medication trends”, Artificial Intelligence in Medicine, (2019)
  • Yaxiong Zeng, Diego Klabjan, “Online adaptive machine learning based algorithm for implied volatility surface modeling”, Knowledge-Based Systems, (2019)
  • Rishabh Joshi, Varun Gupta, Xinyue Li, Yue Cui, Ziwen Wang, Yaser Norouzzadeh Ravari, Diego Klabjan, Rafet Sifa, Azita Parsaeian, Anders Drachen, Simon Demediuk, “A Team Based Player Versus Player Recommender Systems Framework for Player Improvement”, Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2019, (2019)
  • Esa M Rantanen, Limor Hochberg, Mingyang Di, Diego Klabjan, “Decluttering Geographic Data View Displays”, Proceedings of the Human Factors and Ergonomics Society Annual Meeting (2018), (2018)
  • Frank Schneider, Ulrich W. Thonemann, Diego Klabjan, “Optimization of battery charging and purchasing at electric vehicle battery swap stations”, Transportation Science, (2018)
  • 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)