Grants per year
Personal profile
Education/Academic qualification
Industrial Engineering, PhD, Georgia Institute of Technology
… → 1999
Applied Mathematics, BS, University of Ljubljana
… → 1994
Research interests
- Deep learning
- Finance
- Healthcare
- Machine learning and artificial intelligence - text analytics
- Optimization
- Transportation
Fingerprint Dive into the research topics where Diego Klabjan is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 2 Similar Profiles
Costs
Engineering & Materials Science
Electric vehicles
Engineering & Materials Science
Integer programming
Engineering & Materials Science
Lot Sizing
Mathematics
Scheduling
Engineering & Materials Science
Inventory control
Engineering & Materials Science
Linear programming
Engineering & Materials Science
Radio frequency identification (RFID)
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Grants 2007 2022
Agile Manufacturing Systems
Semiconductor Research Corporation
6/1/19 → 5/31/22
Project: Research project
Agile manufacturing systems
Industrial plants
Availability
Silicon
Steady flow
Unsupervised Data Extraction from Graphs and Data Plots
Semiconductor Research Corporation
12/1/17 → 3/31/20
Project: Research project
Knowledge management
Planning
Industry
Deep learning
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
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
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
2
Citations
(Scopus)
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)
4
Citations
(Scopus)
Predicting ICU readmission using grouped physiological and medication trends
Xue, Y., Klabjan, D. & Luo, Y., Apr 1 2019, In : Artificial Intelligence In Medicine. 95, p. 27-37 11 p.Research output: Contribution to journal › Article
Intensive care units
Intensive Care Units
Logistic Models
Statistics
Aptitude
The trails of Just Cause 2: Spatio-temporal player profiling in open-world games
Aung, M., Demediuk, S., Sun, Y., Tu, Y., Ang, Y., Nekkanti, S., Raghav, S., Klabjan, D., Sifa, R. & Drachen, A., Aug 26 2019, Proceedings of the 14th International Conference on the Foundations of Digital Games, FDG 2019. Khosmood, F., Pirker, J., Apperley, T. & Deterding, S. (eds.). Association for Computing Machinery, 41. (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access
Cluster analysis
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