The Aalto Systems and Services Engineering Analytics (AaltoSEA) Group concentrates and consolidates research activities, resources, results, and collaborations on Systems, Software and Data Service Engineering Analytics.

Engineering Analytics

Engineering analytics is concerned with the techniques and tools for desiging, monitoring, analyzing, and optimizing functions, performance, data quality, elasticity, and uncertainties associated with systems, software, data and services. . In our work, we focus on engineering analytics for: Systems (IoT, Cloud, and Edge Systems), Software (Middleware, Protocols, and Tools) , Data (Processing Models and Analytics), Services (Data Marketplace, Service Models, APIs, and Configuration). We apply our engineering analytics techniques to various applications, including smart cities, smart agriculture, enterprises, e-science, logistics, robotics, and e-health. See some high-level ideas in this presentation.


we focus on emerging complex distributed systems covering cloud systems, IoT, edge/fog systems, cyber-physical systems and social-cyber-physical systems. Some of our novel concepts are elastic systems, IoT Cloud systems and the ensembles of IoT, Cloud and Networks


We focus on system software, middleware, tools and applications in the IoT, cloud, edge/fog, cyber-physical systems, and social-cyber-physical systems. Application domains are smart agriculture, smart city, e-science, and industrial internet. Some recent tools are IoT management, Uncertainty Testing for CPS, and IoT Cloud uncertainties


We focus on data models and data analytics, including various types of data in complex distributed systems that are gathered, processed and provisioned under different services. Some our novel concepts are elastic data analytics, Quality of Analytics, and incidents in big data


Services offer functions built on capabilities of the above-mentioned systems, software and data. We focus on novel technical service models (data-as-a-service, IoT services, e-science services, and several application-specific services), service API and execution management, and dynamic business models (e.g. pay-per-use) for consumers. Some of our novel conconcepts are Data-as-a-Service, data contracts for data marketplaces, human sensing data marketplace, and IoT data marketplaces


Open PhD/Postdoc positions: Software Systems and Engineering Analytics for Big Data in IoT, Edge and Cloud Systems

Open teaching assistant positions for Big Data Platforms 2019

Duc-Hung Le

Master Students

  • Kreics Krists: Quality of Analytics Management for Big Data pipelines (with Sellforte)
  • Henriksson Oscar: Apros simulation development in cloud computing (industry-based thesis with Fortum)
  • Minh Duc Ta: Blockchain services development
  • Dániel Füvesi: Big IoT data analytics incidents (TU Wien)
  • Daniel Hopfer: Data lake for cloud forensics (TU Wien)

Current visitors

Adrian Orive Oneca (IKERLAN)

Past visitors

Liang Zhang (Fudan University), The-Vu Tran (Da Nang University), Huu-Hung Huynh (Da Nang University), Nam Huynh (HoChiMinh City University of Technology)

Past members

Postdocs: Dr. Bunjamin Memishi, Dr. Luca Berardinelli, Dr. Georgiana Copil, Dr. Daniel Moldovan,
Master Students: Filip Rydzi, Michael Hammerer, Lingfan Gao, Juraj Cik, Florin Balint, Manfred Halper, Matthias Karan, Peter Klein


Our GitHub prototypes: https://github.com/rdsea

Our Docker Hub: https://hub.docker.com/u/rdsea/

Concepts & Prototypes

Publications & Theses

See our full list here. Three recent publications:

Events & News

1 Feb 2019

The team moves to Aalto University

we are now based on Aalto University, Finland

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15 October 2018

ACM IoT 2018

We gave a tutorial on dynamic solutions for IoT interoperability at ACM IoT 2018

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19-20 Aug 2016

Talk at Workshop on IoT/Cloud-based CPS at Fudan University, Shanghai, China

Luca Berardinelli gives a talk about Modeling, Provisioning, Deployment of IoT/Cloud-based CPS at Fudan University, Shanghai, China Aug 19-20 2016.

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