World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6418
World Ranking
8911
National Ranking
3792

Overview

Diego Klabjan is affiliated with Northwestern University in the United States and has contributed extensively to the field of computer science, with a focus on artificial intelligence and related subfields. Their body of work spans multiple domains including computer vision and pattern recognition, signal processing, management science and operations research, and industrial and manufacturing engineering.

Their recent published papers include:

  • Efficient Architecture Search for Continual Learning, 2022, IEEE Transactions on Neural Networks and Learning Systems
  • Subset selection for multiple linear regression via optimization, 2020, Journal of Global Optimization
  • Open-Set Recognition with Gaussian Mixture Variational Autoencoders, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • The Impact of the Mini-batch Size on the Variance of Gradients in Stochastic Gradient Descent, 2020, arXiv (Cornell University)
  • Diminishing Batch Normalization, 2022, IEEE Transactions on Neural Networks and Learning Systems

The scientist collaborates frequently with several coauthors, including:

  • Jean Utke (20 coauthored papers)
  • Yuan Luo (7 coauthored papers)
  • Tom Overman (5 coauthored papers)
  • Jaeyeon Jang (5 coauthored papers)
  • Alexander Cao (4 coauthored papers)

Publication venues where Diego Klabjan has multiple contributions include:

  • arXiv (Cornell University), 60 publications
  • 2021 IEEE International Conference on Big Data (Big Data), 4 publications
  • IEEE Transactions on Neural Networks and Learning Systems, 3 publications
  • Expert Systems with Applications, 3 publications
  • 2022 IEEE International Conference on Big Data (Big Data), 3 publications

The main fields of study covered by the scientist are:

  • Computer Science (166 publications)

Within computer science, the primary subfields of Diego Klabjan's research include:

  • Artificial Intelligence (106 publications)
  • Computer Vision and Pattern Recognition (33 publications)
  • Signal Processing (17 publications)
  • Management Science and Operations Research (12 publications)
  • Industrial and Manufacturing Engineering (7 publications)

Key topics explored through their work are:

  • Domain Adaptation and Few-Shot Learning (30 publications)
  • Music and Audio Processing (18 publications)
  • Advanced Bandit Algorithms Research (16 publications)
  • Topic Modeling (16 publications)
  • Neural Networks and Applications (16 publications)
  • Anomaly Detection Techniques and Applications (14 publications)
  • Privacy-Preserving Technologies in Data (14 publications)

Best Publications

  • Warehousing and Analyzing Massive RFID Data Sets

    H. Gonzalez;Jiawei Han;Xiaolei Li;D. Klabjan

  • Airline Crew Scheduling

    Cynthia Barnhart;Amy M. Cohn;Ellis L. Johnson;Diego Klabjan

  • Classification-based financial markets prediction using deep neural networks

    Matthew Dixon;Diego Klabjan;Jin Hoon Bang

  • Robust Airline Crew Pairing: Move-up Crews

    Sergey Shebalov;Diego Klabjan

  • Airline Crew Scheduling with Time Windows and Plane-Count Constraints

    Diego Klabjan;Ellis L. Johnson;George L. Nemhauser;Eric Gelman

  • An agent-based decision support system for electric vehicle charging infrastructure deployment

    Timothy Sweda;Diego Klabjan

  • Single machine multi-product capacitated lot sizing with sequence-dependent setups

    Bernardo Almada-Lobo;Diego Klabjan;Maria Antonia Carravilla;Jose Fernando Oliveira

  • Solving Large Airline Crew Scheduling Problems: Random Pairing Generation and Strong Branching

    Diego Klabjan;Ellis L. Johnson;George L. Nemhauser;Eric Gelman

  • Robust stochastic lot-sizing by means of histograms

    Diego Klabjan;David Simchi-Levi;Miao Song

  • Simultaneous vehicle routing and charging station siting for commercial Electric Vehicles

    Owen Worley;Diego Klabjan;Timothy M. Sweda

  • Large-Scale Models in the Airline Industry

    Diego Klabjan

  • Integrated Airline Fleeting and Crew-Pairing Decisions

    Rivi Sandhu;Diego Klabjan

  • Finding minimum-cost paths for electric vehicles

    Timothy M. Sweda;Diego Klabjan

  • Adaptive Routing and Recharging Policies for Electric Vehicles

    Timothy M. Sweda;Irina S. Dolinskaya;Diego Klabjan

  • Fully Polynomial Time Approximation Schemes for Stochastic Dynamic Programs

    Nir Halman;Diego Klabjan;Chung-Lun Li;James B. Orlin

  • Robust Airline Scheduling Under Block-Time Uncertainty

    Milind Sohoni;Yu-Ching Lee;Diego Klabjan

  • Modeling lotsizing and scheduling problems with sequence dependent setups

    Luis Guimarães;Diego Klabjan;Bernardo Almada-Lobo

  • A Fully Polynomial-Time Approximation Scheme for Single-Item Stochastic Inventory Control with Discrete Demand

    Nir Halman;Diego Klabjan;Mohamed Mostagir;Jim Orlin

  • Optimal Recharging Policies for Electric Vehicles

    Timothy M. Sweda;Irina S. Dolinskaya;Diego Klabjan

  • Improving the Expected Improvement Algorithm

    Chao Qin;Diego Klabjan;Daniel Joseph Russo

  • Track 10: Modeling, Simulation, Emissions and Control Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations

    Owen Worley;Diego Klabjan

Frequent Co-Authors

Anders Drachen
Anders Drachen University of Southern Denmark
George L. Nemhauser
George L. Nemhauser Georgia Institute of Technology
Bernardo Almada-Lobo
Bernardo Almada-Lobo University of Porto
Ellis L. Johnson
Ellis L. Johnson Georgia Institute of Technology
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Hani S. Mahmassani
Hani S. Mahmassani Northwestern University
Chung-Lun Li
Chung-Lun Li Hong Kong Polytechnic University

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