Department of Electrical Engineering and Automation

Information Technologies in Industrial Automation

The engineering of software-intensive automation systems is the research focus in our group.
We investigate enablers of future smart factories (Industry 4.0 & 5.0) from the industrial manufacturing, continuous processes, energy management, and human-centric perspectives.
Industrial gripper picture

The focus areas of research in our group are various aspects of information technology applications in industrial automation. We investigate enablers for future smart factories, as a critical part of the concept commonly known as Industry 4.0. Besides, we lead the development of the Aalto Factory of the Future demonstrator.

Among our topics of interest are:

  1. How to control future factories by networks of wirelessly connected microcomputers? And how to develop software for such networks? The exceptional complexity of software development in the manufacturing and process industry inspires us to look for methods of plug-and-play software composition or its automatic generation.
  2. The applications of artificial intelligence techniques in industrial environments for recognizing or predicting dangerous situations and process uncertainties.
  3. Virtual twins of industrial systems, such as simulation models of individual processes and entire plants. Future factories will demand a higher degree of safety and security, achievable by applying modern methods of behavior analysis, relying on the enormous processing power of distributed computing and supercomputers.
  4. Research on the safety and security of current and future energy systems, including nuclear automation.
  5. Enablers for energy automation. The main focus is on the Internet of Energy - the IT-enabled energy production and exchange infrastructure based on prosumers. Smart grid research interests are multi-agent control and security and integration of applications such as smart lighting. 
  6. Human-centric production systems that include real-time workflow and workspace optimization, the interaction of the human workers with AGVs and cobots, and ergonomic aspects of flexible collaborative manufacturing.

We are involved in research projects funded by Academy of Finland, Business Finland, EIT Manufacturing, the European Union, the Finnish Nuclear Waste Management Fund (VYR), and other funding organizations. The group collaborates with many research partners around the globe. Find more details on our research website.

Professor Valeriy Vyatkin is the leader of the group.



Valeriy Vyatkin - Professor
Tommi Karhela - Visiting professor in computer simulation technology
Seppo Sierla   - University lecturer
Ilkka Seilonen - Research scientist
Udayanto Atmojo - Staff scientist
Taneli Hölttä   - Innovation advisor

Doctoral candidates

Pranay Jhunjhunwala
Polina Ovsiannikova
Mikhail Kolesnikov
Tuojian Lyu
Mohammad Arash Azangoo
Jifei Deng
Rakshith Subramanya
Ronal Bejarano Rodriguez
Niko Karhula
Harri Aaltonen

Graduated doctoral candidates:

Igor Buzhinskii  
Thesis: Combined use of formal methods for reliability assurance of safety-critical software systems
Defended: 28/06/2019

Gerardo Santillán Martínez
Thesis: Simulation-based digital twins of industrial process plants: A semi-automatic implementation approach
Defended: 07/06/2019

Christian Giovanelli
Thesis: Aggregating domestic energy storage resources to participate in frequency containment reserves
Defended: 15/03/2019

Olli Kilkki
Thesis: Optimizing Demand Response of Aggregated Residential Energy Storages
Defended: 10/12/2018

Evgeny Nefedov
Thesis: Collaborative energy management systems: design and evaluation for intelligent buildings, electric vehicles and street lighting
Defended: 27/04/2018

Research Projects

Latest publications

Residual-Enhanced Physics-Guided Machine Learning With Hard Constraints for Subsurface Flow in Reservoir Engineering

Haibo Cheng, Yunpeng He, Peng Zeng, Valeriy Vyatkin 2024 IEEE Transactions on Geoscience and Remote Sensing

Toolset Development for Modelling Sympathetic Phenomenon and its Detection by a Neural Network

Nikolai Galkin, Chen Wei Yang, Nicholas Etherden, Math Bollen, Valeriy Vyatkin, Yiming Wu 2024 2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference, ONCON 2023

Enabling Professionals for Industry 5.0

Rui Pinto, Miroslav Žilka, Thalie Zanoli, Mikhail V. Kolesnikov, Gil Gonçalves 2024 PROCEDIA COMPUTER SCIENCE

Digital Twins for Process Industries

Seppo Sierla 2024 Handbook of Digital Twins

Debugging approach for IEC 61499 control applications in FBME

Daniil Akifev, Tatiana Liakh, Polina Ovsiannikova, Radimir Sorokin, Valeriy Vyatkin 2023 2023 IEEE 32nd International Symposium on Industrial Electronics, ISIE 2023 - Proceedings

Metrics and methods for robustness evaluation of neural networks with generative models

Igor Buzhinsky, Arseny Nerinovsky, Stavros Tripakis 2023 Machine Learning

Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells

Haibo Cheng, Shichao Li, Peng Zeng, Valeriy Vyatkin 2023 2023 IEEE 32nd International Symposium on Industrial Electronics, ISIE 2023 - Proceedings

Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data

Haibo Cheng, Yunpeng He, Peng Zeng, Shichao Li, Valeriy Vyatkin 2023 IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
More information on our research in the Aalto research portal.
Research portal
  • Published:
  • Updated: