Modeling, Identification, and Control in Biological and Biomedical Systems
The research activity in this area concerns the development of general methodologies of modelling, estimation and optimal control theory, as well as their application in the study of biomedical and biological systems. Indeed, researches on biomedical applications were performed since the early 70’s with regard to biomechanics, prostheses and modelling of cellular growth.
1. Measurement policy in optimal filtering and control problems;
2. Statistical modelling of rethinal data for diagnostic purposes;
3. Modelling and Identification of tumour spheroids response to radiations;
4. Analysis and modelling of glucose and lipid metabolism and their interaction;
5. Estimation of cerebral connectivity in humans by means of structural and functional models;
6. Implementation of devices for Brain Computer Interface based on parameters of the estimated cortical activity or on the real-time analysis of video-sequences;
7. Medical image analysis, in particular aimed to develop segmentation methods able to enhance the retrieved information from different kind of images (mammographic data, pupil and liver tissue images etc.);
8. Computational optimization in applicative topics of systems biology;
9. Optimal density remodeling for stiffened lightweight structures.
The future activity of the group will mainly focus on the research on the optimal measurement times in the filtering problems, the study of the mechanisms on the basis of insulin secretion and on the insulin resistance; the investigation about the possible application of the Brain computer Interface techniques in the rehabilitation of stroke subjects; the utilization of the neuroengineering tools in the field of the economy/marketing; the research of optimal policies for tumour radiotherapy, the statistical procedures for automatic diagnosis of retinal pathologies¸ the analysis of the bone remodeling by finite element analysis and the optimization of its topology; the computational methods for the analysis of genome wide expression data and the topological features and criticalities in metabolic networks.
Integrazione multimodale di dati EEG, MEG e fMRI per la stima dell’attività e connettività corticale nell’uomo
Studio, progetto e realizzazione di algoritmi efficienti di classificazione mediante reti neurali artificiali di immagini di provini metallografici di ghisa sferoidale; modelli dinamici basati su reti neurali artificiali di fenomeni di frattura