Computational and Process Engineering

CAPE Research Foci

Applied Mathematics and Statistics

One of the core research areas at the department of Computational and Process Engineering is applied mathematics and statistics. We have a worldwide unique concentration of expertise on uncertainty quantification and inverse problems. More specifically, our methodological research includes problem areas such as non-parametric or parametric statistical inverse problems, hierarchical models, MCMC, optimization, stochastic (partial) differential equations and chaotic systems. We drive towards interdisciplinary science: we collaborate with large-scale interdisciplinary research infrastructures (satellite missions, European Southern Observatory, European Incoherent Scatter Radar EISCAT3D), research institutes and several industrial and financial companies. Our team is part of the Centre of Excellence in Inverse Modelling and Imaging granted by the Academy of Finland.

Research group on Uncertainty Quantification and Inverse Problems

Computer Vision and Pattern Recognition (CVPRL)

LUT Computer Vision and Pattern Recognition Laboratory (CVPRL) educates computer vision and pattern recognition experts and develops computationally intelligent information processing methods. The goal is to engineer useful and significant value-added applications, especially using digital image processing and analysis. For example, our research is focuses on machine vision systems for process industry, and medical image analysis for the efficient healthcare of eye diseases.

Our main objective is to carry out high quality research on computer/machine vision and modelling, machine learning, and pattern recognition. The laboratory also serves industry as an expert organization, performs applied research and educates experts in its research fields. In the education, LUT CVPRL offers the Computer Vision and Pattern Recognition major subject in the Degree Program in Computational Engineering (bachelor, master and doctoral studies).

Our research interests include visual inspection, computer/machine vision, medical image analysis and colour science, focusing on object detection and recognition, industrial machine vision, retinal image analysis, spectral image analysis. LUT CVPRL has been selected several times as an LUT Center of Excellence in Research and is associated with Academy of Finland's Center of Excellence in Research in Inverse Mathematics.

Computer Vision and Pattern Recognition Laboratory


Intensification of processes is currently one the most important trends in the field of chemical engineering. Its aim is to improve the efficiency of manufacture methods.

New, intensified processes are radically smaller in size and often also safer and more eco-friendly, and they save energy.  Innovativeness is typical of intensification. Process development does not refer to small improvements to processes, e.g. computational optimisation, but rather to rethinking of the entire process.

Research focuses on the development of new manufacture methods and facilities for process manufacturing. Key topic areas in this sector include intensification of processes, modelling and simulation, methodology of design, safety of processes and development of new process machines, especially multiphase reactors.

Research in the area of process development is carried out by the unit process development research group. The research focuses on biorefineries and the paper industry. The research is applied research, but there is a growing focus on achieving a comprehensive understanding of surface and interface phenomena and the development of new analysis methods.

Biorefineries are the future

Due to the depletion of fossil fuel materials, the importance of refining bio-based materials has increased worldwide. The utilisation raw materials is often hindered by their nonhomogeneous nature or the impurities they contain.

The LUT School of Engineering Science is particularly focused on the development of products achieved through biorefining separation and purification, either as a finished product or for further processing. The School has carried out research for the sugar and sweetener industry and, in recent years, particularly in the development and improvement of forest biorefinery processes.

We examine separation processes in aqueous solutions, organic solvents, and ionic liquids. We also examine the further processing of biorefinery products into final products, such as packaging coatings or membranes, as well as the development of analytical methods for chemical compounds.

Digitalisation in Chemical Engineering

Digitalisation in changing the way of work in Chemical Engineering, and it is taking place in two-thirds of process re-engineering activities these days. In terms of digitalising operations to gain further efficiency and productivity, these efforts have been largely focused on production, plant maintenance, supply chain and the like within the chemical industry. In particular digitalisation is likely to change the way the process industries work with the potential of big data and its analysis making the operations and the supply chain much more responsive. In addition, it is improving innovation process in developing new products and on line innovation analytics. Digitalisation does not concern only industrial environment. Environmental monitoring is also going to digitalizing monitoring systems and analytics.

Data analytics, such as real-time analyses of incoming data, also called streaming analytics, is one major benefit of digitalization. LUT has special competence in analysis of such process and environmental data. The group has special feature as link combining chemical, engineering, and (data) analytics skills. The research has its roots in chemometrics or environmetrics, and has covered a large competence field in various industrial and environmental cases over the last three decades.

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Professor Lasse Lensu