Salman Toor
Universitetslektor vid Institutionen för informationsteknologi; Beräkningsvetenskap
- Telefon:
- 018-471 10 12
- Mobiltelefon:
- 073-703 15 39
- E-post:
- salman.toor@it.uu.se
- Besöksadress:
- Hus 10, Regementsvägen 10
- Postadress:
- Box 524
751 20 UPPSALA
- Akademiska meriter:
- Docent
- CV:
- Ladda ned CV
Kort presentation
Salman Toor is an Associate Professor in Scientific Computing at Uppsala University. He is an expert in the field of distributed computing infrastructures and applied machine learning. Toor is the co-chair of the Scientific Machine Learning (SciML) research group at Uppsala University and co-founder and CTO at Scaleout Systems AB. He has supervised and reviewed more than forty masters thesis projects and is currently the principal supervisor of two Ph.D students.
Nyckelord
- Distributed computing infrastructures; Federated machine learning; System scalability and performance
Publikationer
Urval av publikationer
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Accelerating Fair Federated Learning: Adaptive Federated Adam
Ingår i IEEE Transactions on Machine Learning in Communications and Networking, s. 1017-1032, 2024
- DOI för Accelerating Fair Federated Learning: Adaptive Federated Adam
- Ladda ner fulltext (pdf) av Accelerating Fair Federated Learning: Adaptive Federated Adam
-
GNN-IDS: Graph Neural Network based Intrusion Detection System
Ingår i Proceedings of the 19th International Conference on Availability, Reliability and Security, 2024
- DOI för GNN-IDS: Graph Neural Network based Intrusion Detection System
- Ladda ner fulltext (pdf) av GNN-IDS: Graph Neural Network based Intrusion Detection System
-
Toward efficient resource utilization at edge nodes in federated learning
Ingår i Progress in Artificial Intelligence, s. 101-117, 2024
- DOI för Toward efficient resource utilization at edge nodes in federated learning
- Ladda ner fulltext (pdf) av Toward efficient resource utilization at edge nodes in federated learning
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Efficient Hierarchical Storage Management Empowered by Reinforcement Learning
Ingår i IEEE Transactions on Knowledge and Data Engineering, s. 5780-5793, 2023
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Scalable federated machine learning with FEDn
Ingår i 2022 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022), s. 555-564, 2022
-
Ingår i GigaScience, s. 1-14, 2021
- DOI för Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit
- Ladda ner fulltext (pdf) av Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit
Senaste publikationer
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Restore: A Reinforcement Learning Approach For Data Migration In Multi-Tiered Storage
Ingår i Proceedings of the ACM on Management of Data, 2026
- DOI för Restore: A Reinforcement Learning Approach For Data Migration In Multi-Tiered Storage
- Ladda ner fulltext (pdf) av Restore: A Reinforcement Learning Approach For Data Migration In Multi-Tiered Storage
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Empowering Data Mesh with Federated Learning
Ingår i 2024 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, BIGDATA, s. 2340-2342, 2024
-
Accelerating Fair Federated Learning: Adaptive Federated Adam
Ingår i IEEE Transactions on Machine Learning in Communications and Networking, s. 1017-1032, 2024
- DOI för Accelerating Fair Federated Learning: Adaptive Federated Adam
- Ladda ner fulltext (pdf) av Accelerating Fair Federated Learning: Adaptive Federated Adam
-
Ingår i Annales des télécommunications, s. 165-178, 2024
- DOI för Federated deep Q-learning networks for service-based anomaly detection and classification in edge-to-cloud ecosystems
- Ladda ner fulltext (pdf) av Federated deep Q-learning networks for service-based anomaly detection and classification in edge-to-cloud ecosystems
-
GNN-IDS: Graph Neural Network based Intrusion Detection System
Ingår i Proceedings of the 19th International Conference on Availability, Reliability and Security, 2024
- DOI för GNN-IDS: Graph Neural Network based Intrusion Detection System
- Ladda ner fulltext (pdf) av GNN-IDS: Graph Neural Network based Intrusion Detection System
Alla publikationer
Artiklar i tidskrift
-
Restore: A Reinforcement Learning Approach For Data Migration In Multi-Tiered Storage
Ingår i Proceedings of the ACM on Management of Data, 2026
- DOI för Restore: A Reinforcement Learning Approach For Data Migration In Multi-Tiered Storage
- Ladda ner fulltext (pdf) av Restore: A Reinforcement Learning Approach For Data Migration In Multi-Tiered Storage
-
Accelerating Fair Federated Learning: Adaptive Federated Adam
Ingår i IEEE Transactions on Machine Learning in Communications and Networking, s. 1017-1032, 2024
- DOI för Accelerating Fair Federated Learning: Adaptive Federated Adam
- Ladda ner fulltext (pdf) av Accelerating Fair Federated Learning: Adaptive Federated Adam
-
Ingår i Annales des télécommunications, s. 165-178, 2024
- DOI för Federated deep Q-learning networks for service-based anomaly detection and classification in edge-to-cloud ecosystems
- Ladda ner fulltext (pdf) av Federated deep Q-learning networks for service-based anomaly detection and classification in edge-to-cloud ecosystems
-
Ingår i Expert systems with applications, 2024
- DOI för Data management of scientific applications in a reinforcement learning-based hierarchical storage system
- Ladda ner fulltext (pdf) av Data management of scientific applications in a reinforcement learning-based hierarchical storage system
-
Toward efficient resource utilization at edge nodes in federated learning
Ingår i Progress in Artificial Intelligence, s. 101-117, 2024
- DOI för Toward efficient resource utilization at edge nodes in federated learning
- Ladda ner fulltext (pdf) av Toward efficient resource utilization at edge nodes in federated learning
-
Efficient Hierarchical Storage Management Empowered by Reinforcement Learning
Ingår i IEEE Transactions on Knowledge and Data Engineering, s. 5780-5793, 2023
-
FedQAS: Privacy-Aware Machine Reading Comprehension with Federated Learning
Ingår i Applied Sciences, 2022
- DOI för FedQAS: Privacy-Aware Machine Reading Comprehension with Federated Learning
- Ladda ner fulltext (pdf) av FedQAS: Privacy-Aware Machine Reading Comprehension with Federated Learning
-
Ingår i GigaScience, s. 1-14, 2021
- DOI för Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit
- Ladda ner fulltext (pdf) av Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit
-
MaRe: Processing Big Data with application containers on Apache Spark
Ingår i GigaScience, 2020
- DOI för MaRe: Processing Big Data with application containers on Apache Spark
- Ladda ner fulltext (pdf) av MaRe: Processing Big Data with application containers on Apache Spark
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On-demand virtual research environments using microservices
Ingår i PeerJ Computer Science, 2019
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BAMSI: a multi-cloud service for scalable distributed filtering of massive genome data
Ingår i BMC Bioinformatics, 2018
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Efficient iterative virtual screening with Apache Spark and conformal prediction
Ingår i Journal of Cheminformatics, 2018
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Ingår i IEEE/ACM Transactions on Computational Biology & Bioinformatics, s. 381-392, 2017
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Ingår i SIAM Journal on Scientific Computing, 2016
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The next-generation ARC middleware
Ingår i Annales des télécommunications, s. 771-776, 2010
Doktorsavhandlingar, sammanläggning
Konferensbidrag
-
Empowering Data Mesh with Federated Learning
Ingår i 2024 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, BIGDATA, s. 2340-2342, 2024
-
GNN-IDS: Graph Neural Network based Intrusion Detection System
Ingår i Proceedings of the 19th International Conference on Availability, Reliability and Security, 2024
- DOI för GNN-IDS: Graph Neural Network based Intrusion Detection System
- Ladda ner fulltext (pdf) av GNN-IDS: Graph Neural Network based Intrusion Detection System
-
Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract
s. 3869-3870, 2023
-
Federated Machine Learning for Resource Allocation in Multi-domain Fog Ecosystems
Ingår i 2023 IEEE 12th International Conference on Cloud Networking, CLOUDNET, s. 290-298, 2023
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Efficient Resource Scheduling for Distributed Infrastructures using Negotiation Capabilities
Ingår i 2023 IEEE 16th International Conference on Cloud Computing (CLOUD), s. 486-492, 2023
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Service-based Federated Deep Reinforcement Learning for Anomaly Detection in Fog Ecosystems
Ingår i 2023 26th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), s. 121-128, 2023
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To test, or not to test: A proactive approach for deciding complete performance test initiation
Ingår i BIG-DATA 2022, s. 4758-4767, 2022
-
Scalable federated machine learning with FEDn
Ingår i 2022 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022), s. 555-564, 2022
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An Evaluation of Container Security Vulnerability Detection Tools
s. 95-101, 2021
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Proactive Autoscaling for Edge Computing Systems with Kubernetes
2021
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DecFL: An Ubiquitous Decentralized Model Training Protocol and Framework Empowered by Blockchain
Ingår i BSCI '21, s. 61-70, 2021
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Towards Smart e-Infrastructures, A Community Driven Approach Based on Real Datasets
Ingår i Proceedings of the 2020 IEEE Green Technologies Conference (GreenTech), s. 109-114, 2020
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Smart Resource Management for Data Streaming using an Online Bin-packing Strategy
Ingår i 2020 IEEE International Conference on Big Data (Big Data), s. 2207-2216, 2020
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Ingår i Benchmarking, Measuring, and Optimizing, s. 335-347, 2020
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Adapting the secretary hiring problem for optimal hot–cold tier placement under top-K workloads
Ingår i Proc. 19th International Symposium on Cluster, Cloud, and Grid Computing, s. 576-583, 2019
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HarmonicIO: Scalable data stream processing for scientific datasets
Ingår i Proc. 11th International Conference on Cloud Computing, s. 879-882, 2018
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Cost-aware application development and management using CLOUD-METRIC
Ingår i Proc. 7th International Conference on Cloud Computing and Services Science, s. 515-522, 2017
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SNIC Science Cloud (SSC): A national-scale cloud infrastructure for Swedish academia
Ingår i Proc. 13th International Conference on e-Science, s. 219-227, 2017
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Scientific analysis by queries in extended SPARQL over a scalable e-Science data store
Ingår i Proc. 9th International Conference on e-Science, s. 98-106, 2013
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Investigating an open source cloud storage infrastructure for CERN-specific data analysis
Ingår i Proc. 7th International Conference on Networking, Architecture, and Storage, s. 84-88, 2012
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Performance and stability of the Chelonia storage system
Ingår i Proc. International Symposium on Grids and Clouds 2012, 2012
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A scalable architecture for e-Science data management
Ingår i Proc. 7th International Conference on e-Science, s. 210-217, 2011
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A Grid-Enabled Problem Solving Environment for QTL Analysis in R
Ingår i Proc. 2nd International Conference on Bioinformatics and Computational Biology, s. 202-209, 2010
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Chelonia — a self-healing storage cloud
Ingår i Proc. 9th Cracow Grid Workshop, s. 5-12, 2010
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A grid portal for genetic analysis of complex traits
Ingår i Proc. 32nd International Convention on Information and Communication Technology, Electronics and Microelectronics, s. 281-284, 2009
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Empowering a flexible application portal with a SOA-based grid job management framework
2008