Faculty Directory
Diego Klabjan

Professor of Industrial Engineering and Management Sciences

Director of Master of Science in Machine Learning and Data Science Program

Director, Center for Deep Learning

Contact

2145 Sheridan Road
Tech E278
Evanston, IL 60208-3109

Email Diego Klabjan

Website

Klabjan's Homepage

Departments

Industrial Engineering and Management Sciences

Affiliations

Master of Science in Machine Learning and Data Science 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 (renamed the Master of Science in Machine Learning and Data Science). 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

Data science, machine learning and artificial intelligence - text analytics, deep learning, federated learning, optimization; transportation, finance, bioinformatics


Selected Publications

  • Overman, Tom; Blum, Garrett; Klabjan, Diego, A Primal-Dual Algorithm for Hybrid Federated Learning, Proceedings of the AAAI Conference on Artificial Intelligence (2024).
  • Gao, Qiang; Luo, Zhipeng; Klabjan, Diego; Zhang, Fengli, Efficient Architecture Search for Continual Learning, IEEE Transactions on Neural Networks and Learning Systems (2023).
  • Cao, Alexander; Utke, Jean; Klabjan, Diego, Early Classifying Multimodal Sequences, Association for Computing Machinery (2023).
  • Koo, Jaehoon; Klabjan, Diego; Utke, Jean, An inverse classification framework with limited budget and maximum number of perturbed samples, Expert Systems with Applications (2023).
  • Cao, Alexander; Klabjan, Diego; Luo, Yuan, Open-set recognition of breast cancer treatments, Artificial Intelligence In Medicine (2023).
  • Wongchaisuwat, Papis; Klabjan, Diego, Truth validation with evidence, Knowledge and Information Systems (2022).
  • Qian, Xin; Sifa, Rafet; Liu, Xuefei; Ganguly, Shreyashi; Yadamsuren, Borchuluun; Klabjan, Diego; Drachen, Anders; Demediuk, Simon, Anomaly Detection in Player Performances in Multiplayer Online Battle Arena Games, Association for Computing Machinery (2022).
  • Ger, Stephanie; Klabjan, Diego; Utke, Jean, Classification Models for Partially Ordered Sequences, Springer Science and Business Media Deutschland GmbH:294-305 (2021).