IMDEA Networks
Dr. Javad DOGANI
Investigador Postdoc
- Afiliación: IMDEA Networks Institute
- MSc: Master's Degree in Computer Engineering- Shiraz University, Iran
- PhD: Doctor's degree in Computer Engineering- Shiraz University, Iran
- Ph.D. Thesis: Workload prediction and autoscaling techniques in cloud computing based on container virtualization
- Ph.D. Supervisor: Dr. Farshad Khunjush
- Puesto anterior: Teaching and Research Assistant at Shiraz University, Iran| Ph.D. Student at Shiraz University, Iran
- Fecha de incorporación: Octubre 2023
- Email: javad.dogani@imdea.org
- Tel: +34 662489337
Biografía
Javad Dogani is a postdoctoral researcher at IMDEA Networks Institute, Madrid, Spain, where he joined the Data Transparency research group in October 2023. His ongoing research pursuits include the development of federated learning models customized to the specific requirements of distributed platforms, such as those employed in edge and fog computing.
Javad received his M.Sc. degree in software engineering from Shiraz University in 2012 and completed his Ph.D. in software engineering from the same university in 2023. Before joining IMDEA, he served as a Teaching and Research Assistant at Shiraz University in Iran for nine months, from January to September 2023. Over the last eight years, he has amassed substantial teaching experience, instructing various computer science courses. He also held the Teaching and Research Assistant position at University of Hormozgan in Bandar-abbas, Iran, from 2014 to 2018.
His main research areas are Distributed Systems, Cloud/Edge/Fog Computing, Federated Deep Learning, Parallel Computing, and Big-Data Processing.
Publicaciones previas
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Auto-scaling techniques in container-based cloud and edge/fog computing: Taxonomy and surveycall_made
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Computer Communications, Volume 209, Pages 120-150, September 2023
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Host load prediction in cloud computing with Discrete Wavelet Transformation (DWT) and Bidirectional Gated Recurrent Unit (BiGRU) networkcall_made
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Computer Communications, Volume 198, Pages 157-174, January 2023
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K-AGRUED: A Container Autoscaling Technique for Cloud-based Web Applications in Kubernetes Using Attention-based GRU Encoder-Decoder J Dogani, F Khunjush, M Seydalicall_made
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Journal of Grid Computing, Volume 20, No 40, December 2022
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Multivariate workload and resource prediction in cloud computing using CNN and GRU by attention mechanismcall_made
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The Journal of Supercomputing, Volume 79, pages3437–3470, 2023
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Cloud service composition using genetic algorithm and particle swarm optimizationcall_made
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2021 11th International Conference on Computer Engineering and Knowledge (ICCKE), October 2021
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A new method to detect attacks on the Internet of Things (IoT) using adaptive learning based on cellular learning automatacall_made
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ETRI Journal, WHILEY, Volume 44, NO. 1, Pages 155-167, December 2021