PhD Students
Ongoing PhD students
- Charles Meyers (WASP).
- Lidia Kidane (WASP).
- Aleksandra Obeso Duque (WASP, Industrial PhD Student, Ericsson Research).
- Oliver Larsson.
- Nayereh Rasouli (WASP).
- Anindya Das (WASP, co-advisor).
- Shutong Jin (WASP, co-advisor, enrolled at KTH).
- Obaidullah Zaland (WASP, co-advisor).
- Zhou Zhou (co-advisor).
Graduated PhD students
- Sourasekhar Banerjee (WASP, co-advisor), Advancing Federated Learning: Algorithms and Use-Cases, 2024.
- Ali A. Rahmanian (Industrial PhD Student, Ericsson Research), Edge Orchestration for
Latency-sensitive Applications, 2024.
- Javad Forough (WASP), Machine Learning for Anomaly Detection in Edge Clouds, 2024.
- Tobias Sundqvist (WASP, Industrial PhD Student, TietoEvry),
Machine Learning-based Diagnostics and Observability in Mobile Networks, 2023.
- Hamid Reza Arkian (co-advisor, University Rennes 1), Resource Management of Data Stream Processing
in Geo-Distributed Environments, 2021.
- Lilly Wu (co-advisor, TU Berlin), Automatic Performance Diagnosis and Recovery in Cloud Microservces, 2021.
- Chanh Nguyen Le Tan (WASP), Location-aware Resource Allocation in Mobile Edge Clouds, 2021.
- Mulugeta Ayalew (co-advisor, University Rennes 1), Automatic Resource Management in Geo-Distributed Multi-Cluster Environments, 2021.
- Lars Larsson, Managing Cloud Resource Scarcity, 2020
- Xuan-Son Vu (co-advisor) Privacy-Guardian: The Vital Need in Machine Learning with Big Data, 2020
- Abel Souza (co-advisor) Autonomous resource management for high performance datacenters, 2020
- Jakub Krzywda, May the Power Be with You: Managing Power-Performance Tradeoffs in Cloud Data Centers, 2019
- William Tärneberg (co-advisor, Lund University), The confluence of Cloud computing, 5G, and IoT in the Fog, 2019
- Amardeep Mehta, Resource allocation for Mobile Edge Clouds, 2018
- Selome Kostentinos Tesfatsion, (co-advisor) Energy-efficient Resource Provisioning for Cloud Data Centers, 2018
- Olumuyiwa Ibidunmoye, Performance Anomaly Detection and Resolution for Autonomous Clouds, 2017
- Gonzalo Rodrigo, HPC Scheduling in a Brave New World, 2017
- Mina Sedaghat, Cluster Scheduling and Management for Large-scale Compute Clouds, 2016
- Ahmed Aleyeldin (Ali-Eldin) Hassan, Workload Characterization, Controller Design, and Performance Evaluation for Cloud Capacity Autoscaling, 2015
- Ewnetu Bayuh Lakew, Autonomous Cloud Resource Provisioning: Accounting, Allocation, and Performance Control, 2015
- Petter Svärd, Dynamic Cloud Resource Management - Scheduling, Migration, and Server Disaggregation, 2014
- Wubin Li, Algorithms and Systems for Virtual Machine Scheduling in Cloud Infrastructures, 2014
- Daniel Espling, Enabling Technologies for Management of Distributed Computing Infrastructures, 2013
- Per-Olov Östberg, Virtual Infrastructures for Computational Science: Software and Architectures for Distributed Job and Resource Management, 2011
- Lars Karlsson (co-advisor), Scheduling of parallel matrix computations and data layout conversion for HPC and Multi-Core Architectures, 2011
- Johan Tordsson, Portable Tools for Interoperable Grids, 2009
- Stefan Johansson (co-advisor), Tools for Control System Design: Stratification of Matrix Pairs and Periodic Riccati Differential Equation Solvers, 2009
- Pedher Johansson (co-advisor), Software Tools for Matrix Canonical Computations and Web-based Software Library Environments, 2006
Graduated Licentiate students
- Chanh Nguyen Le Tan, Autonomous Resource Management for Mobile Edge Clouds, 2019.
- Xuan-Son Vu, (co-advisor) Privacy-awareness in the era of Big Data and machine learning, 2019
- Jakub Krzywda, Analysing, Modelling and Controlling Power-Performance Tradeoffs in Data Center Infrastructures, 2017
- Olumuyiwa Ibidunmoye, Performance Problem Diagnosis in Cloud Infrastructures, 2016
- Selome Kostentinos Tesfation, (co-advisor) Energy-efficient Resource Provisioning for Cloud Data Centers, 2016
- Lars Larsson, Placement and Monitoring of Orchestrated Cloud Services, 2015
- William Tärneberg (co-advisor, Lund University), Performance modelling and simulation of the Mobile Cloud Network, 2015
- Mina Sedaghat, Capacity Management Approaches for Compute Clouds, 2013
- Ahmed Aleyeldin (Ali-Eldin) Hassan, Capacity Scaling for Elastic Compute Clouds, 2013
- Ewnetu Bayuh Lakew, Managing Resource Usage and Allocations in Multi-Cluster Clouds, 2013
- Petter Svärd, Live VM Migration - Principles and Performance, 2012
- Wubin Li, Virtual Machine Placement in Cloud Enviroments, 2012
- Daniel Espling, Metadata Management in Multi-Grids and Multi-Clouds, 2011
- Per-Olov Östberg, Architectures, Design Methodologies, and Service Composition Techniques for Grid Job and Resource Management, 2009
- Lars Karlsson (co-advisor), Blocked and Scalable Matrix Computations - Packed Cholesky, In-Place Transposition, and Two-Sided Transformations, 2009
- Johan Tordsson, Decentralized resource brokering for heterogeneous grid environments, 2006
- Peter Gardfjäll, Capacity Allocation Mechanisms for Grid Environments, 2006
- Stefan Johansson, (co-advisor)Stratification of Matrix Pencils in Systems and Control: Theory and Algorithms, 2004
And where did they go?
The graduated PhD students and the postdocs leaving the group have taken some very interesting paths.
Most of them are still in research, but a remarkably large fraction of them do this in industry rather than academia,
e.g., at IBM Research (Dublin), IBM Advanced Analytics Center (Calgary), Apple (San Jose, CA), Red Hat (Madrid),
and five at Ericsson Research (Stockholm, Luleå, Montreal). PhD students going to Academia are now found at Carnegie Mellon University (US), University of Massachusetts Amherst (US), Chalmers University of Technology (Sweden), and Umeå University.
Also a large group of them just crossed the street to our own spinn-off, Elastisys.
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