MVDSI
Max van der StoelInstitute
All research groups

DSG

Distributed Systems & Data Science

The Distributed Systems & Data Science Group conducts research at the intersection of edge computing, federated learning, wireless mesh networks, and applied AI. The group collaborates with leading European institutions including UPC BarcelonaTech, IST Lisbon, and Uppsala University.

The Distributed Systems and Data Science Group (DSG) addresses pressing challenges across computer systems and data science. We aim to advance the abstractions, mechanisms, and techniques for building distributed, intelligent, and high-performing systems — making technology more robust, secure, and accessible. By developing innovative programming models, distributed computing services, and AI-driven solutions, we help organizations and individuals navigate today’s complex digital infrastructure.

Our active research clusters are:

Embedded Machine Learning and Edge Computing 

Edge computing brings computation closer to where data is generated — mobile devices, sensors, and users — enabling low-latency, privacy-preserving, and efficient processing. Our work focuses on the intersection of edge computing and artificial intelligence, particularly for resource-constrained environments such as IoT and micro-clouds. We explore challenges in adaptability, scalability, security, and intelligent resource usage at the network edge, building systems capable of on-device learning and context-aware decision-making.

Focus areas:

  • Adaptive Federated Learning at the Edge
  • Edge Intelligence for Real-time Decision Making
  • AI-powered Resource Optimization in Edge & Fog Systems
  • Security, Privacy & Trust in Edge-based AI Applications
  • Resource allocation in Edge & Fog Computing

 Projects:

Large Language Models & Generative AI

LLMs and generative AI are transforming how humans interact with information, systems, and each other. Our research investigates how to train, adapt, and deploy large-scale language models efficiently and responsibly — from fine-tuning to domain-specific applications — with a focus on low-resource languages, privacy preservation, and real-world deployment constraints.

Focus areas:

  • Efficient Fine-tuning and Adaptation of LLMs
  • Performance Evaluation of Public and Private LLMs
  • Privacy, Fairness, and Safety in Generative AI
  • LLM-based Systems for Decision Support and Knowledge Management

 Projects:

Blockchain and Distributed Ledger Technologies

Blockchain and distributed ledgers are redefining trust, transparency, and automation in digital systems. Our research examines the technical, governance, and performance aspects of blockchain, as well as its application across finance, IoT, healthcare, and logistics.

Focus areas:

  • Blockchain Interoperability, Governance, Scalability and Performance
  • Payment Systems using Blockchain Technology
  • DLT/blockchain Applications in Areas such as IoT, Logistics and Health

 Projects:

QoS in Wireless Mesh Networks

Wireless Mesh Networks (WMNs) extend connectivity through a mesh of interconnected wireless nodes, offering resilience and coverage over large areas. We focus on quality of service (QoS), service placement, and performance optimization in distributed and mobile wireless systems.

Focus areas:

  • Integration of LoRa Technology for Long-range, Low-power IoT Connectivity
  • Micro-cloud QoS in wireless mesh networks
  •  Service deployment and placement in wireless mesh networks
  • Performance evaluation of wireless networks

Projects:

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