Carlos Perez-Galvan's scientific contributions

Publications (2)

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Batch processes show several sources of variability, from raw materials' properties to initial and evolving conditions that change during the different events in the manufacturing process. In this chapter, we will illustrate with an industrial example how to use machine learning to reduce this apparent excess of data while maintaining the relevant...
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In the literature, machine learning (ML) and artificial intelligence (AI) applications tend to start with examples that are irrelevant to process engineers (e.g. classification of images between cats and dogs, house pricing, types of flowers, etc.). However, process engineering principles are also based on pseudo-empirical correlations and heuristi...


... AI involves several methodological domains, such as reasoning, knowledge representation, solution search, and the basic paradigm of machine learning (ML) among them. In the last few years, especially since the introduction of AlphaGo, ML has been greatly developed in the field of industrial chemistry and chemical engineering, thus greatly helping the development of pharmaceuticals and fine chemicals, thus reducing time and cost [3][4][5]. So far, much of the literature has summarized the application of machine learning algorithms in the chemical industry ( Figure 2) [6]. ...