Salman Toor
Senior Lecturer/Associate Professor at Institutionen för informationsteknologi; Beräkningsvetenskap
- Telephone:
- +46 18 471 10 12
- Mobile phone:
- +46 73 703 15 39
- E-mail:
- salman.toor@it.uu.se
- Visiting address:
- Hus 10, Lägerhyddsvägen 1
- Postal address:
- Box 337
751 05 UPPSALA
- Academic merits:
- Docent
- CV:
- Download CV
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Short presentation
Salman Toor is 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 Integrative Scalable Computing Lab (ISCL) at Uppsala University and co-founder and CTO at Scaleout Systems AB. He has supervised and reviewed more than forty master thesis projects and is currently the principal supervisor of two Ph.D students.
Keywords
- big data
- cloud computing
- distributed computing infrastructures
- federated machine learning
- system scalability and performance
Biography
Salman Toor earned his Masters and PhD in Scientific Computing from Uppsala University. In 2014, Toor finished his postdoctoral research from CMS program, Helsinki Institute of Physics, Finland. From 2015-2017, Toor was employed as a researcher in the Department of Information Technology, Uppsala University and as a senior cloud architect at Swedish National Infrastructure for Computing (SNIC). Toor is the co-chair of the Integrative Scalable Computing Lab (ISCL) at Uppsala University and co-founder and CTO at Scaleout Systems AB. Toor is one of the lead architects of the FEDn framework, designed and developed for scalable federated machine learning. Toor is a co-PI of the Gigacow project and a named researcher in the HASTE and SustAinimal projects. Together with extensive research experience, Toor has over 15 years of teaching experience in different international institutions. He has designed and developed both masters and PhD level courses in the field of distributed computing infrastructures.
Research
Projects:
- HASTE: Hierarchical Analysis of Spatial and Spatial and Temporal Data
- Cost-aware Application Development and Management using CLOUD-METRIC
- GROOT: Infrastructure_Security-as-a-Service (ISaaS)
- HarmonicIO: A Stream-based Solution for Scalable Data Analysis
- A Flexible Computational Framework Using R and Map-Reduce
- A Scalable Infrastructure for CMS Data Analysis
- Secure Cloud Connectivity for Scientific Applications
- Chelonia: A Self-healing Distributed Store
For details click here.
Publications
Selection of publications
- Scientific analysis by queries in extended SPARQL over a scalable e-Science data store (2013)
- Investigating an open source cloud storage infrastructure for CERN-specific data analysis (2012)
- Managing Applications and Data in Distributed Computing Infrastructures (2012)
- Empowering a flexible application portal with a SOA-based grid job management framework (2008)
Recent publications
- Data management of scientific applications in a reinforcement learning-based hierarchical storage system (2024)
- Service-based Federated Deep Reinforcement Learning for Anomaly Detection in Fog Ecosystems (2023)
- Efficient Resource Scheduling for Distributed Infrastructures using Negotiation Capabilities (2023)
- Efficient Hierarchical Storage Management Empowered by Reinforcement Learning (2023)
- Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract (2023)
All publications
Articles
- Data management of scientific applications in a reinforcement learning-based hierarchical storage system (2024)
- Efficient Hierarchical Storage Management Empowered by Reinforcement Learning (2023)
- FedQAS (2022)
- To test, or not to test (2022)
- Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit (2021)
- MaRe (2020)
- On-demand virtual research environments using microservices (2019)
- Efficient iterative virtual screening with Apache Spark and conformal prediction (2018)
- BAMSI (2018)
- A flexible computational framework using R and Map-Reduce for permutation tests of massive genetic analysis of complex traits (2017)
- MOLNs (2016)
- QTL as a service (2016)
- The next-generation ARC middleware (2010)
Books
- Managing Applications and Data in Distributed Computing Infrastructures (2012)
- Managing applications and data in distributed computing infrastructures (2010)
Conferences
- Service-based Federated Deep Reinforcement Learning for Anomaly Detection in Fog Ecosystems (2023)
- Efficient Resource Scheduling for Distributed Infrastructures using Negotiation Capabilities (2023)
- Efficient Hierarchical Storage Management Empowered by Reinforcement Learning Extended Abstract (2023)
- Scalable federated machine learning with FEDn (2022)
- An Evaluation of Container Security Vulnerability Detection Tools (2021)
- Proactive Autoscaling for Edge Computing Systems with Kubernetes (2021)
- DecFL (2021)
- Apache Spark Streaming, Kafka and HarmonicIO (2020)
- Towards Smart e-Infrastructures, A Community Driven Approach Based on Real Datasets (2020)
- Smart Resource Management for Data Streaming using an Online Bin-packing Strategy (2020)
- Adapting the secretary hiring problem for optimal hot–cold tier placement under top-K workloads (2019)
- HarmonicIO (2018)
- Cost-aware application development and management using CLOUD-METRIC (2017)
- SNIC Science Cloud (SSC) (2017)
- Scientific analysis by queries in extended SPARQL over a scalable e-Science data store (2013)
- Performance and stability of the Chelonia storage system (2012)
- Investigating an open source cloud storage infrastructure for CERN-specific data analysis (2012)
- A scalable architecture for e-Science data management (2011)
- A Grid-Enabled Problem Solving Environment for QTL Analysis in R (2010)
- Chelonia — a self-healing storage cloud (2010)
- A grid portal for genetic analysis of complex traits (2009)
- Empowering a flexible application portal with a SOA-based grid job management framework (2008)
Reports
