Department of Chemical and Metallurgical Engineering

Process control and automation

The group led by Prof. Francesco Corona and Prof. Iiro Harjunkoski is a trans-disciplinary research team that builds up on chemical engineering, applied mathematics and computer science. Our research is at the interface of automatic control, machine learning, and optimisation, we emphasise the computational and inferential thinking of process systems.
CMET_PCA group

We develop fundamental methodologies and concrete tools of process control and process systems engineering that are capable of sensing, learning, reasoning, and actuating on chemical and physical systems based on observational data and domain knowledge.

The research develops on four foundational pillars:

  1. Data
  2. Phenomenological and probabilistic modelling
  3. Statistical inference/learning
  4. Optimal control/decision

The formal framework for modelling and control is given as a model of the system in which the uncertainties associated with our knowledge and the measuring process are clearly stated. An important objective in our research is the design and control of models that capture complex dynamics.

Open positions
  • MSc Thesis:  None
  • BSc Thesis: None

Related content:

Professorship strengthens the cooperation of ABB and Aalto in Industrial Internet solutions

Dr. Iiro Harjunkoski has been appointed Adjunt Professor at the School of Chemical Engineering.

Iiro Harjunkoski

Latest publications:

Block particle filters for state estimation of stochastic reaction-diffusion systems

José Augusto F. Magalhães, Otacilio B. L. Neto, Francesco Corona 2023 IFAC-PapersOnLine

A Bayesian inferential sensor for predicting the reactant concentration in an exothermic chemical process

Teemu Ikonen, Samuli Bergman, Francesco Corona 2023 Chemometrics and Intelligent Laboratory Systems

End-effect mitigation in multi-period stochastic programming of energy storage operations

Teemu Ikonen, Dongho Han, Jay H. Lee, Iiro Harjunkoski 2023 33rd European Symposium on Computer Aided Process Engineering

Likelihood Maximization of Lifetime Distributions With Bathtub-Shaped Failure Rate

Teemu J. Ikonen, Francesco Corona, Iiro Harjunkoski 2023 IEEE TRANSACTIONS ON RELIABILITY

Stochastic programming of energy system operations considering terminal energy storage levels

Teemu J. Ikonen, Dongho Han, Jay H. Lee, Iiro Harjunkoski 2023 Computers and Chemical Engineering

Evidence of waste management impacting severe diarrhea prevalence more than WASH : An exhaustive analysis with Brazilian municipal-level data

Anni Juvakoski, Henrik Rantanen, Michela Mulas, Francesco Corona, Riku Vahala, Olli Varis, Ilkka Mellin 2023 Water Research

Combining Machine Learning with Mixed Integer Linear Programming in Solving Complex Scheduling Problems

Iiro Harjunkoski, Teemu Ikonen 2022 14th International Symposium on Process Systems Engineering

Design of an Event-Driven Rescheduling Algorithm via Surrogate-based Optimization

Teemu Ikonen, Keijo Heljanko, Iiro Harjunkoski 2022 14th International Symposium on Process Systems Engineering

Surrogate-based optimization of a periodic rescheduling algorithm

Teemu Ikonen, Keijo Heljanko, Iiro Harjunkoski 2022 AIChE Journal

Cross-domain fault diagnosis through optimal transport for a CSTR process

Eduardo Fernandes Montesuma, Michela Mulas, Francesco Corona, Fred Maurice Ngole Mboula 2022 IFAC-PapersOnLine
More information on our research in the Aalto research portal.
Research portal
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