The goal of the LSDS group is to support the design and implementation of tomorrow's large-scale distributed systems. We investigate new abstractions and infrastructures for building scalable, robust and secure data-intensive applications.

Current Projects

BOSS
A Bring-Your-Own-Kernel DBMS
Big Data Processing
CloudCAP
Compartments and Cloud-Native Applications
Cloud Computing
Faasm
High performance serverless computing
Big Data ProcessingServerless
FractOS
Secure and Efficient Disaggregated Systems
Cloud ComputingSystems Security
KungFu
Adaptive Distributed Machine Learning
Machine Learning
LightSaber
Multi-core Window-Based Stream Processing
Big Data Processing
Teechain
A Secure Blockchain Payment Network
Systems Security
Ako
Decentralised Deep Learning
Machine Learning
ASIA
Adaptive Publish/Subscribe Systems
Cloud Computing
CloudFilter
Confinement of Sensitive Data
Cloud Computing
CloudSafetyNet
End-to-End Cloud Security
Systems Security
Crossbow
Scalable Multi-GPU Deep Learning
Machine Learning
DISSP
Dependable Stream Processing Systems
Big Data ProcessingCloud Computing
HARNESS
Heterogeneous Cloud Computing
Cloud Computing
ITA-DSM
Mobile Stream Processing
Big Data ProcessingNetworking
MDF
Meta-Dataflows
Big Data Processing
Medea
Heterogenous Application Scheduling
Cloud Computing
MobiCloud
Mobile Edge Computing
Cloud ComputingNetworking
Multicore-FSM
Parallel Finite State Machines
Big Data Processing
NaaS
Application-Specific Network Services
Cloud ComputingNetworking
SABER
Hybrid Stream Processing
Big Data ProcessingMachine Learning
SEEP
Stateful Big Data Processing
Big Data Processing
SERECA
Hardware-Assisted Cloud Security
Cloud ComputingSystems Security
SGX-LKL
Linux Binaries in SGX Enclaves
Systems Security
SmartFlow
Secure Event-Based Middleware
Systems Security
SymNV
Symbolic Network Verification
Networking
Ukairo
Scalable Internet Detouring
Cloud ComputingNetworking

Recent Publications

Using Recursive Attestation to Scale Trust in Modern Heterogeneous Cloud Architectures (APSys)
in ACM SIGOPS Asia-Pacific Workshop on Systems
Yaoxin Jing, Michael Steiner, Anjo Vahldiek-Oberwagner, Mona Vij, and Lluís Vilanova
Cephalopod–Virtual Data Model Composition through Partial Query Translation
in Conference on Innovative Database Research
Pirk, Holger and Loughlin, David Conor
[PDF]
Tempo: Compiled Dynamic Deep Learning with Symbolic Dependence Graphs
in 31st ACM Symposium on Operating Systems Principles (SOSP)
Pedro F. Silvestre and Peter Pietzuch
MORE PUBLICATIONS

The LSDS Group

Marios Kogias
Assistant Professor
Peter Pietzuch
Professor
Holger Pirk
Associate Professor
Lluís Vilanova
Associate Professor
Munir Geden
Post-doctoral Researcher
Andrea Piermarteri
Post-doctoral Researcher
Vasily Sartakov
Post-doctoral Researcher
Huanzhou Zhu
Post-doctoral Researcher
Guo Li
Research Assistant
Konstantinos Fertakis
PhD Student
Alessandro Fogli
PhD Student
Jinnan Guo
PhD Student
Yaoxin Jing
PhD Student
Ahmad Khazale
PhD Student
Fotis Kounelis
PhD Student
Scofield Liu
PhD Student
David Loughlin
PhD Student
Eleftheria Mappoura
PhD Student
Domagoj Margan
PhD Student
Hubert Mohr-Daurat
PhD Student
Carlos Segarra
PhD Student
Pedro Silvestre
PhD Student
Yanda Tao
PhD Student
Marcel Wagenländer
PhD Student
Otto White
PhD Student
Takahiro Shinagawa
Visitor
Farzad Mohammadi
PhD Student

Open Positions

PhD position in Big Data Management: Data Compression

Studentship: Untaxed bursary of £16,553 per annum (2017/18 figure including London weighting plus home/EU fees)

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PhD position in Big Data Management: Auto-tuning for modern hardware

Studentship: Untaxed bursary of £16,553 per annum (2017/18 figure including London weighting plus home/EU fees)

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PhD positions in Computer Systems for BigData and Data Science

Studentships available: Untaxed bursary of £16,553 per annum

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Post-Doctoral Researcher in Distributed Systems, Systems, Databases

We have multiple post-doctoral positions in the LSDS group in the areas of distributed systems, software systems, database and networking.

Contact Us

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Interested in joining LSDS? How to apply