Atieh Khodadadi, M.Sc. Atieh-Khodadadi

Atieh Khodadadi, M.Sc.

  • Karlsruhe Institute of Technology
    Institute AIFB
    KIT-Campus South
    Kaiserstr. 89
    D-76133 Karlsruhe

Bio

Atieh Khodadadi ist Doktorandin am Institut für Angewandte Informatik und Formale Beschreibungsverfahren, Karlsruher Institut für Technologie, Deutschland. Ihre Forschung konzentriert sich auf die Nutzung digitaler Zwillinge zur Verbesserung der Energieeffizienz in Fertigungssystemen, mit besonderem Schwerpunkt auf Energie, Modellierung und Simulation sowie Data Mining.

Forschungsinteressen

• Modeling and Simulation • Data-driven Simulation • Data Analytics • Digital Twins • Energy Efficiency • Process Mining

Publikationen


2024
Multi-flow Process Mining for Comprehensive Simulation Model Discovery
Khodadadi, A.; Lazarova-Molnar, S.
2024. ACM - Proceedings of the 14th International Conference on Information Communication and Management, Association for Computing Machinery (ACM)
Essential Data Requirements for Industrial Energy Efficiency with Digital Twins: A Case Study Analysis
Khodadadi, A.; Lazarova-Molnar, S.
2024. The 7th International Conference on Emerging Data and Industry
2023
Towards Sustainable Manufacturing: Digital Twins for Enhanced Energy Efficiency
Khodadadi, A.; Lazarova-Molnar, S.
2023, Juli 3. 11th EUROSIM Simulation Congress (2023), Amsterdam, Niederlande, 3.–5. Juli 2023
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Khodadadi, A.; Ghanbari Bousejin, N.; Molaei, S.; Kumar Chauhan, V.; Zhu, T.; Clifton, D. A.
2023. Sensors, 23 (14), Art.-Nr.: 6571. doi:10.3390/s23146571
2021
Classification of audio codecs with variable bit-rates using deep-learning methods
Khodadadi, A.; Molaei, S.; Teimouri, M.; Zare, H.
2021. Digital Signal Processing, 110, Article no: 102952. doi:10.1016/j.dsp.2020.102952
2020
Classification of Audio Codecs with Variable Bit- Rates
Khodadadi, A.; Teimouri, M.
2020. 10th International Conference on Computer and Knowledge Engineering (ICCKE 2020), 050–054, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCKE50421.2020.9303637
2019
Dataset for file fragment classification of audio file formats
Khodadadi, A.; Teimouri, M.
2019. BMC Research Notes, 12, Article no: 819. doi:10.1186/s13104-019-4856-1