Diego Klabjan

2145 Sheridan Road, IEMS
Evanston, IL 60208

Director, Master of Science in Machine Learning and Data Science
​Director, Center for Deep Learning
Tel: 847-491-0663
Email: d-klabjan at northwestern dot edu
www.klabjan.dynresmanagement.com
Picture

Vita


General Interests: Machine Learning in the Areas of
  • Methodology
  • Deep learning
  • Text analytics
  • Federated learning
  • Healthcare
  • Finance

Education
  • Ph. D. in Algorithms, Combinatorics, and Optimization
           Georgia Institute of Technology, Atlanta, GA (1999)
                      Dissertation: Topics in Airline Crew Scheduling and Large Scale Optimization (Advisors: George Nemhauser and Ellis Johnson)
  • B.S. in Applied Mathematics (1994)
           University of Ljubljana, Ljubljana, Slovenia
                     Dissertation: A Randomized Algorithm for Computing the Volume of a Convex Set (Advisor: Bojan Mohar)

Work Experience

  • 2012-present: Professor, Northwestern University, Department of Industrial Engineering and Management Sciences, Evanston, Illinois
  • 2007-2012: Associate professor, Northwestern University, Department of Industrial Engineering and Management Sciences, Evanston, Illinois
  • 2006-2007: Associate professor, University of Illinois at Urbana-Champaign, Department of Civil and Environmental Engineering, Urbana, Illinois
  • 2005-2006: Visiting professor, MIT, Department of Civil and Environmental Engineering, Cambridge, Massachusetts
  • 1999-2005: Tenure-track assistant professor, University of Illinois at Urbana-Champaign, Department of Mechanical and Industrial Engineering, Urbana, Illinois

Awards
  • 2019 Pushing the Boundaries of the Possible, Intel's Outstanding Researcher Award
  • ​2017 IEEE International Conference on Information Reuse and Integration, Best Student Paper (by Ph.D student Xiaofeng Zhu)
  • 2015 INFORMS Computing Society, Best Student Paper (by Ph.D student Young Woong Park)
  • 2015 APDIO/IO Award, Best Thesis in years 2013-2014 by Portuguese OR Society (by Ph.D. student Luis Guimarães)
  • 2015 Isabel Themido Award, best paper in 2013-2014 by Portuguese OR Society (by Ph.D. student Luis Guimarães)
  • 2011 Student Paper Contest, Railway Application Section of INFORMS, Second prize, Charlotte, NC (by post-doctoral student Conrado Borraz)
  • 2006 Best Student Paper, The 22nd International Conference on Data Engineering, Atlanta, GA (by graduate student Hector Gonzales)
  • 2004 Anna Valicek Medal Winner, AGIFORS, Singapore (by graduate student Rivi Sandhu)
  • 2000 First Prize Transportation Science Section Dissertation Prize, INFORMS, Washington DC
  • 1994 Preseren's Award for the Best Undergraduate Thesis, University of Ljubljana, Slovenia

Refereed Publications
  1. C. Kim, Y. Kim and D. Klabjan. Scale Invariant Power Iteration. To appear in Journal of Machine Learning Research. 2019. 
  2. A. Cao, D. Klabjan, and Y. Luo. Open-Set Recognition of Breast Cancer Treatments. To appear in Artificial Intelligence in Medicine. 2022. 
  3. Y. Ma and D. Klabjan, Diminishing Batch Normalization. To appear in IEEE Transactions on Neural Networks and Learning Systems, 2022.
  4. ​J. Koo, D. Klabjan and J. Utke. Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples. To appear in Expert Systems With Applications,
     2020
  5. Q. Gao, Z. Luo and D. Klabjan, Efficient Architecture Search for Continual Learning. To appear in  IEEE Transactions on Neural Networks and Learning Systems 2022.
  6. P. Wongchaisuwat and D. Klabjan. Truth Validation with Evidence. To appear in Knowledge and Information Systems 2022.
  7. N. Craig, N. DeHoratius and D. Klabjan, Execution Quality and Chargeback Penalties in Retail Supply Chains. To appear in Journal of Operations Management 2020.
  8. Y.W. Park and D. Klabjan, Subset Selection for Multiple Linear Regression via Optimization. To appear in Journal of Global Optimization 2020.
  9. J. Yang and D. Klabjan, Bayesian Active Learning for Choice Models with Deep Gaussian Processes. To appear in Transactions on Intelligent Transportation Systems 2019.
  10. C. Kim and D. Klabjan, A Simple and Fast Algorithm for L1-norm Kernel PCA. To appear in Transactions on Pattern Analysis and Machine Intelligence 2019.
  11. C. Borraz-Sanchez, D. Klabjan, and A. Uygur. An Approach for the Railway Multi-terrritory Dispatching Problem.To appear in Transportation Science 2019.
  12. Y. Yang, S. Shebalov and D. Klabjan. Semi-supervised Learning for Discrete Choice Models. To appear in Transactions on Intelligent Transportation Systems 2018.
  13. Y. Zeng and D. Klabjan. Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling. To appear in Knowledge-Based Systems 2018.
  14. Y. Xue, Y. Luo and D. Klabjan. Predicting  ICU  readmission  using  grouped  physiological  and  medication  trends. To appear in Artificial Intelligence in Medicine 2018.
  15. D. Klabjan, M. Di, L. Sha and P. Lucey. Large-scale Adversarial Sports Play Retrieval with Learning to Rank. To appear in ACM Transactions on Knowledge Discovery from Data ​2017. 
  16. Y. Zeng and D. Klabjan. Portfolio Optimization of American Options. To appear in Journal of Computational Finance 2017. 
  17. Y.W. Park and D. Klabjan. Bayesian Network Learning via Topological Order. To appear in Journal of Machine Learning Research 2017.
  18. Richards CT, Wang B, Markul E, Albarran F, Rottman D, Aggarwal NT, Lindeman P, Stein-Spencer L, Weber JM, Pearlman KS, Tataris KL, Holl JL, Klabjan D, Prabhakaran S. Identifying Key Words in 9-1-1 Calls for Stroke: A Mixed Methods Approach. To appear in Prehospital Emergency Care 2017.
  19. F. Schneider, U. Thonemann, D. Klabjan. Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations. To appear in Transportation Science 2017.
  20. C. Borraz-Sanchez, J. Ma, D. Klabjan, E. Pasalic, M. Aref. Algebraic Modeling in Datalog. In Declarative Logic Programming: Theory, Systems, and Applications. Editors: Michael Kifer and Yanhong A. Liu. Publisher: Association for Computing Machinery and Morgan & Claypool 2017.
  21. D. Zhang and D. Klabjan. Optimization for Gate Re-assignment. To appear in Transportation Research Part B 2016.  
  22. J. Mays and D. Klabjan. Optimization of Time-Varying Electricity Rates. To appear in The Energy Journal 2016.
  23. M. Dixon, D. Klabjan, and J.H. Bang. Classication-based Financial Markets Prediction using Deep Neural Networks. To appear in Journal of Algorithmic Finance 2016.
  24. T. Sweda, I. Dolinskaya, and D. Klabjan. Adaptive Routing and Recharging Policies for Electric Vehicles. To appear in Transportation Science 2016.    
  25. Y.W. Park, Y. Jiang, D. Klabjan, and L. Williams. Algorithms for Generalized Cluster-wise Linear Regression. To appear in INFORMS Journal on Computing 2016.
  26. P. Wongchaisuwat, D. Klabjan and S. Jonnalagadda. A Semi-supervised Learning Approach to Enhance Health Care Community-based Question Answering: A case Study in Alcoholism. To appear in JMIR Medical Informatics 2016.    
  27. Y-W. Park and D. Klabjan. An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning. To appear in Machine Learning 2016. 
  28. Seth, D. Klabjan and P. Ferreira, A Novel Local Search Integer-Programming-Based Heuristic for PCB Assembly on Collect-and-Place Machines. To appear in Mathematical Programming Computation 2015.
  29. N. Craig, J. Yan, N. DiHoratius and D. Klabjan.  An Analysis of Fulfillment Errors in a Retail Distribution Center. To appear in Journal of Operations Management 2015. 
  30. T. Sweda, I. Dolinskaya, and D. Klabjan. Adaptive Routing and Recharging Policies for Electric Vehicles. To appear in Transportation Science 2015.
  31. C. Pun, D. Klabjan, F. Karaesmen, S. Shebalov. Itinerary-Based Nesting Control with Upsell. To appear in Journal of Revenue and Pricing Management. 2015.
  32. S. Shebalov, Y. W. Park, and D. Klabjan (2015), Lifting for Mixed Integer Programs with Variable Upper Bounds. Discrete Applied Mathematics (2015) Volume 186, pp 226-250.
  33.  Y. Zeng, D. Klabjan, and J. Arinez (2014), Distributed Solar Renewable Generation: Option Contracts with Renewable Energy Credit Uncertainty. To appear in Energy Economics.
  34. C. Kim, D. Klabjan, D Simchi-Levi (2012), Optimal expediting policies for an inventory system with expiry. To appear in Production and Operations Management. 2015.
  35. A. Lavin, D. Klabjan (2014). Clustering Time-Series Energy Data from Smart Meters. To appear in Energy Efficiency.
  36. L. Guimaraes, D. Klabjan and B. Almada-Lobo, Modeling lotsizing and scheduling problems with sequence dependent setups. European Journal of Operational Research 239 (2014) 644-662.
  37. C. Almeder, D. Klabjan, and B. Almada-Lobo (2011), Lead Time Considerations for the Multi-Level Capacitated Lot-sizing Problem. To appear in European Journal of Operational Research (2009).
  38. Y-W Park and D. Klabjan (2013), Lot Sizing with Minimum Order Quantity. To appear in Discrete Applied Mathematics. (2013).
  39. D. Klabjan, W. Olszewski, and A. Wolinsky (2014), Attributes. To appear in Games and Economic Behavior.
  40. A. Drachen, J. Riley, S. Baskin,  D. Klabjan. Going Out of Business: Auction House Behavior in the Massively Multi-Player Online Game Glitch. To appear in Entertainment Computing, 2014.
  41. N. Halman, D. Klabjan, C-L. Li, J. Orlin and D. Simchi-Levi (2014), Fully Polynomial Time Approximation Schemes for Convex and Monotone Stochastic Dynamic Programming. To appear in SIAM Journal on Discrete Mathematics.     
  42. T. Sweda and D. Klabjan (2014), An Agent-Based Information System for Electric Vehicle Charging Infrastructure Deployment, To appear in ASCE Journal of Infrastructure Systems.
  43. A. Wald, M. Harmon and D. Klabjan. Structural Deplaning via Simulation and Optimization. To appear in Journal of Air Transport Management  (2013).
  44. D. Wang, S. Shebalov, D. Klabjan. (2013) Attractiveness-Based Airline Network Models with Embedded Spill and Recapture. To appear in Journal of Airline and Airport Management.
  45. P. Pei, D. Klabjan (2012), Approximations to Auctions of Digital Goods with Share-averse Bidders, To appear in Electronic Commerce Research and Applications.
  46. L. Guimaraes, B. Klabjan, B. Almada-Lobo (2013), Pricing, Relaxing and Fixing under Lotsizing and Scheduling, European Journal of Operational Research 230 (2013) 399-411.
  47. D. Klabjan and C. Borraz, Optimal Placement of Reconfigurable Optical Add/Drop Multiplexers with Packing, Blocking, and Signal Loss, Computer Networks 57 (2013) 1443-1458.
  48. F. Schneider and D. Klabjan, Inventory Control in Multi-channel Retail, European Journal of Operational Research 227 (2013) 101-111.
  49. M. Song, D. Klabjan, D. Simchi-Levi, Robust Stochastic Lot-sizing by Means of Histograms, Production and Operations Management 22 (2013) 691-710.
  50. J. Ahn, O. de Weck, Y. Gang and D. Klabjan, The Generalized Location Routing Problem with Profits, European Journal of Operational Research 223 (2012) 47-59.
  51. Seth, D. Klabjan and P. Ferreira (2012), Analyses of Advanced Iterated Tour Partitioning Heuristics for Generalized Vehicle Routing Problems. To appear in Networks. 
  52. L. Guimaraes, D. Klabjan, B. Almada-Lobo, Annual Production Budget in the Beverage Industry. International Scientific Journal Engineering Applications of Artificial Intelligence 25 (2012) 229-241.
  53. P. Bless, D. Klabjan, and S. Chang , Automated Knowledge Source Selection and Service Composition. Computational Optimization and Applications 52 (2012) 507-535.
  54. Y. Zhao and D. Klabjan, A Polyhedral Study of Lot-sizing with Supplier Selection. Discrete Optimization 9 (2012) 65-76.
  55. D. Adelman and D. Klabjan, Computing Near Optimal Policies in General Joint Replenishment. INFORMS Journal on Computing 24 (2012) 148-164. 
  56. M. Sohoni, Y-C. Lee, D. Klabjan, Block Time Estimation and Robust Airline Scheduling. Transportation Science 45 (2011) 451-464
  57. D. Klabjan and J. Pei, In-store One-to-one Marketing. Journal of Retailing and Consumer Services 18 (2011) 64-73.
  58. S. Chang, D. Klabjan, and T. Vossen, Optimal Radio Frequency Identification Deployment in a Supply Chain Network. International Journal of Production Economics 125 (2010) 71-83. 
  59. L. Schenk and D. Klabjan, Intra Market Optimization for Express Package Carriers with Station to Station Travel and Proportional Sorting. Computers & Operations Research 37 (2010) 1749-1761.
  60. J. Pei and D. Klabjan, Inventory Control in Serial Systems under Radio Frequency Identification. International Journal of Production Economics 123 (2010) 118-136. 
  61. S. Choo, D. Klabjan and D. Simchi-Levi, Multi-ship Crane Sequencing with Yard Congestion Constraints. Transportation Science 44 (2010) 98-115. 
  62. H. Gonzalez, J. Han, H. Cheng, X. Li, D. Klabjan and T. Wu, Modeling Massive RFID Datasets: A Gateway-Based Movement-Graph Approach. IEEE Transactions on Knowledge and Data Engineering 22 (2010) 90-104. 
  63. B. Almada-Lobo, D.  Klabjan, M.A. Carravilla and J.F. Oliveira, Multiple Machine Multi-Item Continuous Setup Lotsizing with Sequence-dependent Setups. Computational Optimization and Applications 47 (2010) 529-552.
  64. L. Schenk and D. Klabjan, Intra Market Optimization for Express Package Carriers. Transportation Science 42 (2008) 530-545. 
  65. N. Halman, D. Klabjan, M. Mostagir, J. Orlin,  D. Simchi-Levi, A Fully Polynomial Time Approximation Scheme for Single-Item Stochastic Inventory Control Problems with Discrete Demand. Mathematics of Operations Research 34 (2009) 674-685
  66. D. Klabjan, Subadditive Approaches in Integer Programming. European Journal of Operational Research 183 (2007) 525-545.
  67. B. Almada-Lobo, D.  Klabjan, M.A. Carravilla, J.F. Oliveira, Single Machine Capacitated Lotsizing Problem with Sequence-dependent Setup Costs and Times. International Journal of Production Research 45 (2007) 4873-4894.
  68. J. Han, H. Gonzales, X. Li, and D. Klabjan, Warehousing and Mining Massive RFID Data Sets, Lecture Notes in Computer Science 4093 (2006) 1-18. 
  69. D. Klabjan and D. Adelman, A Convergent Infinite Dimensional Linear Programming Algorithm for Deterministic Semi-Markov Decision Processes on Borel Spaces. Mathematics of Operations Research 32 (2007) 528-550.
  70. P. Bless, D. Klabjan, and S. Chang, Heuristics for Automated Knowledge Source Selection and Service Composition. Computers and Operations Research 35 (2008) 1292-1314.
  71. R. Sandhu and D. Klabjan, Fleeting with Passenger and Cargo Origin-Destination Booking Control. Transportation Science 40 (2006) 517-528.
  72. R. Sandhu and D. Klabjan, Integrated Airline Fleeting and Crew Pairing Decisions. Operations Research 55 (2007) 430-438.
  73. D. Klabjan and D. Adelman, Existence of Optimal Policies for Semi-Markov Decision Processes Using Duality for Infinite Linear Programming, SIAM Journal on Control and Optimization 44 (2006) 2104-2122.
  74. S. Shebalov and D. Klabjan, Robust Airline Crew Pairing: Move-up Crews, Transportation Science 40 (2006) 300-312. 
  75. S. Shebalov and D. Klabjan, Sequence Independent Lifting for Mixed Integer Programs with Variable Upper Bounds. Mathematical Programming 105 (2006) 523-561.
  76. P.N. Bless, S.G. Kapoor, R.E. DeVor, and D. Klabjan, An Algorithmic Strategy for Automated Development of Multi-component Software Tools for Virtual Manufacturing. Journal of Manufacturing Science and Engineering 127 (2005) 866-874.
  77. D. Adelman and D. Klabjan, Existence of Optimal Policies and Duality in Generalized Joint Replenishment. Mathematics of Operations Research 30 (2005) 28-50.
  78. D. Klabjan, A Practical Algorithm for Computing the Subadditive Dual Function for Set Partitioning, Computational Optimization and Applications 29 (2004) 347-368. 
  79. A. Makri and D. Klabjan, Algorithms for Source-to-all Maximum Cost to Time Ratio Problem in Acyclic Networks. Networks 42 (2003) 1-14.
  80. D. Klabjan, E.L. Johnson, and G.L. Nemhauser, Airline Crew Scheduling with Time Windows and Plane Count Constraints, Transportation Science 36 (2002) 337-348.
  81. D. Klabjan and G.L. Nemhauser, A Polyhedral Study of  Integer Variable Upper Bounds. Mathematics of Operations Research 27 (2002) 711-739.
  82. A. Arora and D. Klabjan, A Model for Budget Allocation in Multi-unit Libraries. Library Collections, Acquisitions, and Technical Services 26 (2002) 423-438.
  83. A. Makri and D.Klabjan, A New Pricing Scheme for Airline Crew Scheduling, INFORMS Journal on Computing 16 (2004) 56-67.
  84. D. Klabjan, E.L. Johnson, and G.L. Nemhauser, Solving Large Airline Crew Scheduling Problems: Random Pairing Generation and Strong Branching, Computational Optimization and Applications 20 (2001) 73-91. 
  85. D. Klabjan, E.L. Johnson, and G.L. Nemhauser, Airline Crew Scheduling with Regularity, Transportation Science 35 (2001) 359-374. 
  86. D. Klabjan, E.L. Johnson, and G.L. Nemhauser, A Parallel Primal-Dual Simplex Algorithm, Operations Research Letters 27 (2000) 47-55.
  87. D. Klabjan and B. Mohar, The Number of Matchings of Low Order in Hexagonal Systems, Discrete Mathematics 186 (1998) 167-175. 
  88. D. Klabjan, C. Tovey, and G.L. Nemhauser, Cover Inequality Separation is NP-hard, Operations Research Letters 23 (1998) 35-40.

Chapters in Books

  • D. Conway and D. Klabjan (2012), Innovation Patterns and Big Data, Forthcoming in Big Data and Business Analytics, Taylor and Francis. Editor J. Liebowitz.
  • Y. Jiang, D. Klabjan, L. Williams (2010), Analytics in Retail. Encyclopedia in Operations Research and Management Sciences, Wiley & Sons. 
  • T. Sweda and D. Klabjan (2010), The Nascent Industry of Electric Vehicles. Encyclopedia in Operations Research and Management Sciences, Wiley & Sons.
  • Y-C. Lee, D. Klabjan, G. Stojkovic (2009), Crew Management Information Systems. In B. Smith and C. Barnhart, editors, Quantitative Problem Solving Methods in the Airline Industry: A Modeling Methodology, Springer Verlag
  • C. Taylor, D. Klabjan, and H. Mamani (2008), Advanced Optimization for Interplanetary Logistics. In O. de-Weck and B. Shisko, editors, Interplanetary Supply Chain Management and Logistics Architecture. 
  • C. Barnhart, A. Cohn, E.L. Johnson, D. Klabjan. G.L. Nemhauser, and P.Vance (2002), Airline Crew Scheduling. In Hall, R.W., editor, Handbook in Transportation Science, Kluwer Scientific Publishers.
  • D. Klabjan (2005), Large-scale Models in the Airline Industry. In G. Desaulniers, J. Desrosiers, M.M. Solomon, editors, Column Generation, Kluwer Academic Publishers.
  • D. Klabjan (2007), Radio Frequency Identification Enabled Business Applications in Supply Chain Management. In T. Blecker  and G. Huang, editors, RFID in Operations and Supply Chain Management: Research and Applications, Erich Schmidt Verlag.

Peer-Reviewed Conference Proceedings
  • T. Joo and D. Klabjan. Improving Self-training under Distribution Shifts via Anchored Confidence with Theoretical Guarantees. NeurIPS. Vancouver, BC, Canada. 2024.
  • B. Fang, T. Vo and D. Klabjan. A Stochastic Large-scale Machine Learning Algorithm for Distributed Features and Observations. IEEE International Conference on Big Data. Washington DC, 2024.
  • C. Kim, Y, Kim, D. Klabjan, and Y. Jambunath. Stochastic Scale Invariant Power Iteration for Kullback-Leibler Divergence Nonnegative Matrix Factorization. IEEE International Conference on Big Data. Washington DC, 2024.
  • Y. Xue, D. Klabjan and J. Utke. Multimodal Learning on Temporal Data. IEEE International Conference on Big Data. Washington DC, 2024.
  • H. Li, D.Klabjan, ​and J.Utke. Unsupervised Video Summarization. 17th Asian Conference on Computer Vision. Hanoi, Vietnam, 2024.
  • Y. Xue, D. Klabjan and J.Utke. S-Omninet: Structured Data Enhanced Universal Multimodal Learning Architecture. International Conference on Machine Learning and Applications. Coral Gabels, 2024. 
  • A. Treviño, J. Utke and D. Klabjan. Multi-Layer Attention-Based Explainability via Transformers for Tabular Data. International Conference on Machine Learning and Applications. Coral Gabels, 2024. 
  • T. Overman, D. Klabjan, and J. Utke. IIFE: Interaction Information Based Automated Feature Engineering. International Conference on Data Mining. Abu Dhabi. 2024.
  • H. Wu and D. Klabjan. Robust Softmax Aggregation on Blockchain based Federated Learning with Convergence Guarantee. IEEE Coins. London, UK. 2024.
  • S. Mu and D. Klabjan. On the Second-Order Convergence of Biased Policy Gradient Algorithms.  ICML, Vienna, Austria 2024.
  • T. Joo and D. Klabjan. IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation. ICML, Vienna, Austria 2024.
  • S. Wang and D. Klabjan. An Ensemble Method of Deep Reinforcement Learning for Automated Cryptocurrency Trading. IEEE International Conference on Blockchain and Cryptocurrency, Dublin, Ireland 2024.
  • G. Blum, R. Doris, D. Klabjan, H. Espinosa and R. Szalkowski. Use of Deep Neural Networks for Uncertain Stress Functions with Extensions to Impact Mechanics. To appear in IEEE’s 9th International Conference on Big Data Analytics, Tokyo, Japan 2023.
  • T. Overman, G. Blum and D. Klabjan. A Primal-Dual Algorithm for Hybrid Federated Learning. AAAI, Vancouver, Canada 2024.
  • Y. Ma and D. Klabjan. Semi-supervised 3D Video Information Retrieval with Deep Neural Network and Bi-directional Dynamic-time Warping Algorithm. IEEE International Conference on Big Data, Sorrento, Italy 2023. 
  • S. Lim, D. Klabjan and M. Shapiro. Feature Acquisition Using Monte Carlo Tree Search. IEEE International Conference on Big Data, Sorrento, Italy 2023.
  • S. Ger, Y. Jambunath and D. Klabjan. Autoencoders and Generative Adversarial Networks for Anomaly Detection for Sequences IEEE International Conference on Big Data, Sorrento, Italy 2023.
  • S. Ger, Y. Jambunath, D. Klabjan, J. Utke. Cohesive Attention-Based Explanations for Sequences and Explainability in Presence of Event Types. IEEE International Conference on Big Data, Sorrento, Italy 2023. 
  • M. Xu and D.Klabjan. Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards. NeurIPS. New Orleans 2023.
  • A. Cao, J. Utke and D. Klabjan. Early Classifying Multimodal Sequences. 25th ACM International Conference on Multimodal Interaction. Paris, France 2023.
  • A. Cao, J. Utke and D. Klabjan. A Policy for Early Sequence Classification. 32nd International Conference on Artificial Neural Networks. Crete, Greece 2023.
  • A. Trevino-Gavito, D. Klabjan, and J.Utke. Gradient-boosted Based Structured and Unstructured Learning. 32nd International Conference on Artificial Neural Networks. Crete, Greece 2023.
  • M. Xu and D. Klabjan. Pareto Regret Analyses in Multi-objective Multi-armed Bandit. International Conference on Machine Learning, Honolulu, HI 2023.
  • G. Ebrahimi and D. Klabjan. Neuron-based pruning of deep neural networks with better generalization using Kronecker factored curvature approximation. International Joint Conference on Neural Networks, Queensland, Australia 2023.
  • X. Qian, M. Kennedy and D. Klabjan. Dynamic Cell Structure via Recursive-Recurrent Neural Networks. IEEE International Conference on Big Data, Osaka, Japan. Virtual due to Covid-19 2022.
  • Y. Xu and D. Klabjan. Open Set Domain Adaptation by Extreme Value Theory. IEEE International Conference on Big Data, Osaka, Japan. Virtual due to Covid-19 2022.
  • Y. Xue, D. Klabjan, and Y. Luo. Aggregation Delayed Federated Learning. IEEE International Conference on Big Data, Osaka, Japan Virtual due to Covid-19 2022.
  • C. Ke, H. Deng, C. Xu, J. Li, X. Gu, B. Yadamsuren, D. Klabjan, R. Sifa, A. Drachen and S. Demediuk. DOTA 2 match prediction through deep learning team fight models. IEEE Conference on Games, Beijing, China, Virtual due to Covid-19 2022.
  • A. Ebrahimi, A. Stec, D. Klabjan, and J. Utke. Nested Multi-Instance Image Classification. International Conference on Pattern Recognition. Montreal 2022.
  • D. Klabjan and X. Zhu. Neural Network Retraining for Model Serving. IEEE International Conference on Big Data,  Virtual due to Covid-19 2021.
  • H. Wu and D. Klabjan, Logit-based Uncertainty Measure in Classification. IEEE International Conference on Big Data,  Virtual due to Covid-19 2021.
  • X. Wang, L. Zhang and D. Klabjan. Keyword-based Topic Modeling and Keyword Selection. IEEE International Conference on Big Data,  Virtual due to Covid-19 2021.
  • Y. Xu and D. Klabjan. Concept Drift and Covariate Shift Detection Ensemble with Lagged Labels. IEEE International Conference on Big Data,  Virtual due to Covid-19 2021.
  • S. Ger, D. Klabjan, and J. Utke. Classification Models for Partially Ordered Sequences. International Conference on Artificial Neural Networks, Virtual due to Covid-19 2021.
  • N. Byanna, G. Ebrahimi and D. Klabjan. Evaluating the Performance of Offensive Linemen in the NFL. ICMLDMSA: 15. International Conference on Machine Learning and Data Mining for Sports Analytics, Virtual due to Covid-19 2021.
  • G. Ebrahimi, C. Ge, D. Klabjan, D. Ladner, and P. Stride. Cirrhosis Mortality Prediction as Classification. 15th International Conference on Health Information Systems and Clinical Decision, Virtual due to Covid-19 2021.
  • X. Qian and D. Klabjan. A Probabilistic Approach to Neural Network Pruning. International Conference on Machine Learning, Virtual due to Covid-19 2021.
  • Y. Xu and D. Klabjan. k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks. International Joint Conferences on Artificial Intelligence (IJCAI), Virtual due to Covid-19 ​2021.
  • G. Ebrahimi, B. Wang and D. Klabjan. Generative Adversarial Nets for Multiple Text Corpora. International Joint Conference on Neural Network (IJCNN), Virtual due to Covid-19  2021.
  • G. Ebrahimi, L. Zhang and D. Klabjan. Layer Flexible Adaptive Computational Time for Recurrent Neural Networks. International Joint Conference on Neural Network (IJCNN), Virtual due to Covid-19  2021.
  • M. Harmon, A. Ebrahimi, D. Klabjan, and P. Lucey. Predicting Shot Making in Basketball using Convolutional Neural Networks Learnt from Adversarial Multiagent Trajectories. International Conference on Computer Science in Sport and Exercise, Istanbul, Turkey 2021
  • A. Cao, Y. Luo and D. Klabjan. Open-Set Recognition with Gaussian Mixture Variational Autoencoders. AAAI, Virtual due to Covid-19  2020.
  • J. Koo, D. Klabjan, and J. Utke. Combined Convolutional and Recurrent Neural Networks for Hierarchical Classification of Images. IEEE International Conference on Big Data, Virtual due to Covid-19 2019.
  • M. Harmon and D. Klabjan. Dynamic Prediction Length for Time Series with Sequence to Sequence Network. ACM International Conference on AI in Finance, New York, NY  2020.
  • J. Koo and D. Klabjan. Improved classification based on Deep Belief Networks (submitted for publication. 29th International Conference on Artificial Neural Networks (ICANN), Bratislava, Slovakia 2020.
  • Y. Xu, D. Rajpathak, I. Gibbs, D. Klabjan. Automatic Ontology Learning from Domain-Specific Short Unstructured Text Data. 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KMIS), Budapest, Hungary 2020.
  • C. Kim and D. Klabjan. Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes. AISTATS, Palermo, Italy 2020.
  • R. Sifa, M. Fedell, N. Franklin, D. Klabjan, S. Ram, A. Venugopal, S. Demediuk, and A. Drachen (2020). Retention Prediction in Sandbox Games with Bipartite Tensor Factorization. Computing Conference, London, UK 2020.
  • M. Harmon and D. Klabjan. Activation Ensembles for Deep Neural Networks. IEEE International Conference on Big Data, Los Angeles, CA 2019.
  • Y. Xue, D. Klabjan, and Y. Luo. Mixture-based Multiple Imputation Models for Clinical Data with a Temporal Dimension. IEEE International Conference on Big Data, Los Angeles, CA 2019.
  • X. Zhu and D. Klabjan. Listwise Learning to Rank by Exploring Unique Ratings. The 13th ACM International Conference on Web Search and Data Mining (WSDM), Houston, TX 2020.
  • S. Demediuk, R. Joshi, Z. Wang, V. Gupta, X. Li, Y. Cui, D. Klabjan, A. Parsaeian, A. Drachen. A Team Based Player Versus Player Recommender Systems Framework for Player Improvement. Australasian Computer Science Week, Sydney, Australia 2019. Best paper award
  • X. Teng, A. Zufle, G. Trajcevski, and  D. Klabjan. Location-Awareness in Time Series Compression. 22nd European Conference on Advances in Databases and Information Systems, Budapest, Hungary 2018.
  • E. M. Rantanen, L. Hochberg, D. Ming, D., and D. Klabjan. Decluttering Geographic Data View Displays. Proceedings of the Human Factors and Ergonomics Society 2018 Annual Meeting, Philadelphia, PA.
  • X. Wang and D. Klabjan. Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations. ICML, Stockholm, Sweden 2018. 
  • A. Drachen, E. Pawlakos, K. Zhai, S. Haran, R. Jha, R. Sifa, and D. Klabjan, Controlling the Crucible: A Novel PvP Recommender Systems Framework for Destiny. Australasian Computer Science Week, Brisbane, Australia 2018.
  • A. Drachen, J. Runge, R. Sifa, M. Pastor, A. Liu, D. J. Fontaine, Y. Chang, and D. Klabjan (2018), To Be or Not to Be… Social: Incorporating Simple Social Features in Mobile Game Customer Lifetime Value Predictions. Australasian Computer Science Week, Brisbane, Australia.
  • C. Qin, D. Russo, and D. Klabjan (2017), Improving the Expected Improvement Algorithm. NIPS, Long Beach, CA.
  • X. Zhu, D. Klabjan, and P. Bless (2017).  Semantic Document Distance Measures and Unsupervised Document Revision Detection. International Joint Conference on Natural Language Processing, Taipei, Taiwan.
  • P. Wognchaisuwat, D. Klabjan, and J. McGinnis (2017). Predicting Litigation Likelihood and Time to Litigate for Patents The 16th International Conference on Artificial Intelligence and Law, London, UK    
  • B. Wang and D. Klabjan (2017). Regularization for Unsupervised Deep Neural Nets. AAIA, San Francisco, CA.
  • Y. Park, D. Klabjan (2014). Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis, IEEE International Conference on Data Mining, Barcelona, Spain.    
  • A. Drachen, E. Lundquist, Y. Kung, P. Rao, D. Klabjan, R. Sifa, and J. Runge (2016). Rapid Prediction of Player Retention in Free-to-Play Mobile Games. The Twelfth Annual AAAI Conference of Artificial Intelligence and Interactive Digital Entertainment, San Francisco, CA.    
  • A. Drachen, J. Green, C. Gray, E. Harik, P. Lu, R. Sifa, and D. Klabjan (2016). Guns and Guardians: Comparative Cluster Analysis and Behavioral Profiling in Destiny. IEEE Computational Intelligence and Games Conference, Santorini, Greece.
  • T. Jeong, D. Klabjan, and J. Starren (2016). Predictive Analytics Using Smartphone Sensors for Depressive Episodes. HIAI, Expanding the Boundaries of Health Informatics using AI, Phoenix, AZ.    
  • B. Wang and D. Klabjan. Time-Dependent Topic Analysis with Endogenous and Exogenous Processes. AAAI Phoenix, AX 2015.
  • M. Dixon, D. Klabjan, and J.H. Bang. Implementing Deep Neural Networks for Financial Market Prediction on the Intel Xeon Phi. Supercomputing, Austin, TX 2015.
  • A. Drachen, D. Klabjan, M. Yancey, D. Chu, J. Maguire, Y. Wang. Skill-Based Differences in Spatio-Temporal Team Behavior in Defense of the Ancients 2. 6th IEEE Consumer Electronics Society Games, Entertainment, Media Conference, Toronto, 2014.
  • E. Ko, D. Klabjan.  Semantic Properties of Customer Sentiment in Tweets. The 28th IEEE International Conference on Advanced Information Networking and Applications. Victoria, Canada, 2014. 
  • O. Worley and D. Klabjan (2012), “Simultaneous Vehicle Routing and Charging Station Siting for Commercial Electric Vehicles”, IEEE International Electric Vehicle Conference, Greenville, NC.
  • T. Sweda and D. Klabjan (2012), “Finding Minimum-Cost Paths for Electric Vehicles”, IEEE International Electric Vehicle Conference, Greenville, NC.
  • T. Sweda and D. Klabjan (2011), “An Agent-Based Decision Support System for Electric Vehicle Charging Infrastructure Deployment,” 7th IEEE Vehicle Power and Propulsion Conference, Chicago, Illinois.
  • O. Worley and D. Klabjan (2011), “Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations,” 7th IEEE Vehicle Power and Propulsion Conference, Chicago, Illinois.
  • S. Ruangpattana, D. Klabjan, J. Arinez, and S. Biller (2011), “Optimization of On-site Renewable Energy Generation for Industrial Sites,” Proceedings of IEEE Power Systems 2011, Phoenix, AZ.
  • C. Cheng, C. Chekuri, and D. Klabjan (2009), “Topology Formation for Wireless Mesh Network Planning,” Proceedings of IEEE Infocom 2009 Mini-conference, Rio de Janeiro, Brazil.
  • N. Halman, D. Klabjan, C-L. Li, J. Orlin, and D. Simchi-Levi (2008), “Fully Polynomial Time Approximation Schemes for Stochastic Dynamic Programs,” Proceedings of ACM-SIAM Symposium on Discrete Algorithms, San Francisco, CA. 
  • J. Han, H. Gonzalez, X. Li, and Diego Klabjan (2006), “Warehousing and Mining Massive RFID Data Sets,” Proceedings of the International Conference on Advanced Data Mining and Applications, Xi'An, China.
  • H. Gonzales, J. Han, X. Li, and D. Klabjan (2006), “Warehousing and Analyzing Massive RFID Data Sets,”  Proceedings of the 22nd International Conference on Data Engineering, Atlanta, GA.
  • D. Klabjan (2002), “A New Subadditive Approach to Integer Programming: Theory and Algorithms,” Proceedings of the 9th Integer Programming and Combinatorial Optimization Conference, 384-400.
  • D. Klabjan and K. Schwan (2001), “Airline Crew Pairing Generation in Parallel,” Proceedings of the 10th SIAM Conference on Parallel Processing for Scientific Computing. 
​
Patents
  • Patent No. 10,467,556, inventor Diego Klabjan, Information systems and methods for deployment of charging infrastructure in support of electric vehicles​.
Magazine Publications
  • M. Blackburn, J. Alexander, J. David Legan and D. Klabjan, Big Data and the Future of R&D Management, Research-Technology Management, 60 (2017), number 5.
  • C. Taylor, M. Song, D. Klabjan, O. de Weck, D. Simchi-Levi, A Mathematical Model for Interplanetary Logistics, Logistics Spectrum 41 (2007), Issue 1, January-March, pages 23-33.
  • D. Klabjan, R. Joshi, Harvesting Smart Grid Benefits, M2M (2009), September-October, page 40.​
Academic Invited Lectures 
  • IIT Madras, Chennai, India (2024)
  • Southwest Jiaotong University, School of AI and Computing, China (2022)
  • Sharif University, Industrial Engineering (2022)
  • University of Ljubljana, Department of Mathematics (2019)
  • University of Illinois Chicago, School of Business (2018)
  • University of Texas, Austin, McCombs School of Business (2018)
  • University of North Carolina, Kenan-Flagler School of Business (2016)
  • University of South Florida, Industrial Engineering (2015)
  • London Imperial College, School of Computing (2014)
  • Hong Kong University, Department of Industrial Engineering (2014)
  • Carnegie Mellon University, Tepper School of Business (2014)
  • University of Chicago, Booth School of Business (2011)
  • Illinois Institute of Technology, Applied Mathematics (2009)
  • University of Colorado, Boulder, School of Business (2008)
  • Texas A&M, Industrial and Systems Engineering (2008)
  • Northwestern University, Kellogg School of Management (2008)
  • Fields Institute, McMaster University (2007) 
  • Ohio State University, Integrated Systems Engineering (2007)
  • University of Wisconsin, Industrial Engineering (2007)
  • MIT, OR Center Seminar Series (2006)
  • University of Illinois at Urbana-Champaign, Department of Aerospace Engineering (2006)
  • Cornell University, Operations Research (2006)
  • Stanford, Management Science and Engineering (2004)
  • Princeton University, Operations Research (2004) 
  • University of Michigan, Industrial and Operations Engineering (2003)
  • University of California, Berkeley, Civil and Environmental Engineering Seminar Series (2002) 
  • MIT, OR Center Seminar Series (2001) 
  • SUNY Buffalo, Industrial Engineering (2000)
  • University of Chicago, Graduate School of Business (2000)
  • Georgia Institute of Technology, Industrial and System Engineering (2000)

Corporate Invited Lectures

  • Cisco, April 2024.
  • Tiger Analytics, January 2024. 
  • Zebra, December 2023.
  • Ford, March 2019.
  • General Motors, August 2016.
  • McDonalds, August 2016. 
  • Schneider, July 2015.
  • Alcatel-Lucent, January, 2013.
  • Amadeus, Nice, France, January 2013.
  • NASA Langley, October 2012.
  • FHWA, Freight & Carbon Footprint: Efforts to Enhance Supply Chain Sustainability, September 2010. 
  • Ford, R&D (2010)
  • United Airlines, Enterprise Optimization (2008)
  • Sabre Holdings, The Research Group (2007)
  • O’Hare Airport, O’Hare Modernization Program (2007)
  • Sears Holdings, Panelist of experts on Logistics Business Practices for Home Delivery (2007)
  • FedEx Express, R&D (2006) 
  • RiverGlass Inc., R&D (2005)
  • Motorola, R&D (2005)
  • Caleb Technologies Corp., R&D (2004)
  • SBS International, R&D (2003)
  • American Airlines, Operations Research (2003)

Ph.D. Students
  • 3 or 4 new every year
  • Shuyang Wang (Goldman Sacks)
  • Mengfan Xu 2024 (University of Massachusetts Armherst)
  • Xin Qian 2022 (Meta)
  • Alex Cao 2023 (United Airlines)
  • Ghani Ebrahimi 2022 (Wells Fargo)
  • Xiaoyi Liu 2022 (Meta)
  • Biyi Fang 2020 (Walmart.com)
  • Yiming Xu 2021 (Facebook)
  • Andrea Trevino-Gavito 2024 (Microsoft)​
  • Stephanie Ger 2021 (Apple)
  • Yintai Ma 2024 (Citadel)
  • Ye Xue 2022 (Meta)
  • Cheolmin Kim 2020 (Google)
  • Jaehoon Koo 2020 (Argonne National Lab)
  • Xiaofeng Zhu 2020 (Microsoft)
  • Alexander Stec 2018 (Allstate)
  • Mark Harmon 2018 (Sloan Kettering Cancer Center)
  • Papis Wongchaisuwat 2017 (Kalasin Univesity)
  • Baiyang Wang 2017 (General Motors)
  • Jie Yang 2017 (Staples)
  • Yaxiong Zeng 2016 (Guggenheim Partners)
  • Mingyang Di 2016 (American Express)
  • Young-Woong Park 2014 (Southern Methodist University)
  • Timothy Sweda 2014 (Schneider)
  • Yue Gang 2013 (Discover Financials)
  • Jinxiang Pei 2012 (Krafts)
  • Chan Seng Pun 2012 (Saber Holdings)
  • Yan Jiang 2012 (Sears)
  • Anupam Seth 2009 (Yahoo!)
  • Chiwon Kim 2008 (Accenture)
  • Patrick Bless 2006 (Intel)
  • Sergey Shebalov 2004 (Sabre Holdings)

Activities

Department Editor of Design and Manufacturing, IIE Transactions
Former President, INFORMS Aviation Section
Memberships
  • Institute for Operations Research and the Management Sciences
  • Mathematical Optimization Society
  • Institute of Industrial Engineers
  • Alfred Sloan Foundation
  • Founding member of Industry Studies Association
  • IEEE
  • Association of Computer Machinery
Associate Editor
  • Naval Research Logistics
  • Operations Research (Area of Optimization)
  • Operations Research (Area of Transportation)
  • IIE Transactions (Department Editor in Manufacturing and Analytics)
Advisory Board member, INFORMS Practice meeting (2009-present)
Main Organizer
  • Conference: The Business of Big Data, San Jose, CA (2014)
  • Workshop: Innovation in Big Data Analytics, San Jose, CA (2012)
  • Workshop: The Greening of Transportation, Evanston, IL (2009)
  • Workshop: Business Intelligence in Transportation, Evanston, IL (2009)
  • Fall INFORMS Meeting Cluster Chair: Scheduling in the Service Sector, Washington DC (2008)
Evanston Mayor’s Wind Farm Committee