Grants per year
Personal profile
Education/Academic qualification
Industrial Engineering, PhD, Georgia Institute of Technology
… → 1999
Applied Mathematics, BS, University of Ljubljana
… → 1994
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Electric vehicles
Engineering & Materials Science
Costs
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Integer programming
Engineering & Materials Science
Scheduling
Engineering & Materials Science
Inventory control
Engineering & Materials Science
Linear programming
Engineering & Materials Science
Radio frequency identification (RFID)
Engineering & Materials Science
electric vehicle
Social Sciences
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Grants 2007 2020
Predoctoral Training Program in Biomedical Data Driven Discovery (BD3)
9/10/15 → 9/9/20
Project: Research project
training program
applied science
engineering science
school
science
NRT-DESE: Training in Data-Driven Discovery - From the Earth and the Universe to the Successful Careers of the Future
Downey, D. C., Kalogera, V., Katsaggelos, A. K., Klabjan, D., Luijten, E., Schmitt, M. H. & van der Lee, S.
4/1/15 → 3/31/20
Project: Research project
student
communication
data mining
twenty first century
data management
Unsupervised Data Extraction from Graphs and Data Plots
Semiconductor Research Corporation
12/1/17 → 11/30/18
Project: Research project
Knowledge management
Planning
Industry
Deep learning
OSCM: An Operating System for Cyberphysical Manufacturing
Cao, J., Ehmann, K. & Klabjan, D.
University of Illinois at Urbana-Champaign, Department of the Army
8/30/16 → 12/31/18
Project: Research project
Scheduling
Planning
Cellular manufacturing
Application programs
Education
Students
Finance
Research Output 1998 2019
A Team Based Player Versus Player Recommender Systems Framework for Player Improvement
Joshi, R., Gupta, V., Li, X., Cui, Y., Wang, Z., Ravari, Y. N., Klabjan, D., Sifa, R., Parsaeian, A., Drachen, A. & Demediuk, S., Jan 29 2019, Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2019. Association for Computing Machinery, a45. (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Recommender systems
Cluster analysis
Online adaptive machine learning based algorithm for implied volatility surface modeling
Zeng, Y. & Klabjan, D., Jan 1 2019, In : Knowledge-Based Systems. 163, p. 376-391 16 p.Research output: Contribution to journal › Article
Learning systems
Computer hardware
Sensitivity analysis
Program processors
Field programmable gate arrays (FPGA)
Competitive multi-agent inverse reinforcement learning with sub-optimal demonstrations
Wang, X. & Klabjan, D., Jan 1 2018, 35th International Conference on Machine Learning, ICML 2018. Krause, A. & Dy, J. (eds.). International Machine Learning Society (IMLS), Vol. 11. p. 8148-8175 28 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Reinforcement learning
Demonstrations
Learning algorithms
Experiments
3
Citations
(Scopus)
Controlling the crucible: A novel PvP recommender systems framework for destiny
Sifa, R., Pawlakos, E., Zhai, K., Haran, S., Jha, R., Klabjan, D. & Drachen, A., Jan 29 2018, Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2018. Association for Computing Machinery, 3167926. (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Information filtering
Recommender systems
Crucibles
Decision making
Location-Awareness in Time Series Compression
Teng, X., Züfle, A., Trajcevski, G. & Klabjan, D., Jan 1 2018, Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings. Benczur, A., Horvath, T. & Thalheim, B. (eds.). Springer Verlag, p. 82-95 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11019 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Location Awareness
Time series
Compression
Data compression
Data Compression