Antonio Brunetti

Antonio Brunetti received the Bachelor Degree in Computer Science and Automation Engineering, and the Master Degree (cum laude) in Computer Science Engineering at the Polytechnic University of Bari. His final dissertation in Human-Computer Interaction concerned the design and implementation of an intelligent system able to modify the living environment of subjects with mild cognitive impairment based on the cognitive event-related potential on the EEG signal.
Subsequently, he worked as Research Fellow at the Polytechnic University of Bari working on GCESYS - "Green Community Efficiency Systems" project dealing with optimization algorithms applied to energy consumptions scheduling in smart buildings with systems supplied by mixed traditional and renewable sources.
Currently, he is a PhD student in Electrical and Information Engineering at the Doctoral School of the Polytechnic University of Bari under the supervision of Prof. Vitoantonio Bevilacqua, working on Decision Support Systems based on biomedical signals for the customization and optimization of diagnosis, prognosis and therapy.
On March 2019 he founded Apulian Bioengineering srl, a spin-off of Polytechnic of Bari, as a shareholder.

IBIO-01/A

Antonio Brunetti is a PhD student in Electrical and Information Engineering at the Doctoral School of the Polytechnic University of Bari. Since 2015 he had several professional experiences includes several collaborations at the Department of Electrical and Information Engineering (DEI) of the Polytechnic University of Bari where he worked on the design and development of intelligent algorithms for image and signal processing, working on different projects, including RESCAP - "Residual Capabilities" (http://rescap.it/), PRE.C.I.O.U.S. - "PREdictive Computer aIded scOring sUpport System" (https://www.preciousproject.it/), RECALL - "Monitoraggio delle Risposte Elettrofisiologiche Correlate ai mutamenti Ambientali prodotti da tecnologia domotica e ambienti immersivi and Living Labs" (http://recall-project.it/) and PRE.MED - "PREdictive MEDicine" project, where he has to design and develop an operating environment for the extraction and processing of morphological features of patients affected by Autosomal Dominant Polycystic Kidney Disease (ADPKD) and to validate the diagnostic classification framework.

His research interests include bioengineering, computer vision and image processing, human-machine interaction and machine learning techniques (neural networks, evolutionary algorithms, deep learning).

Currently, he teaches Health Information Systems at the Polytechnic University of Bari (Master Degree in Medical System Engineering) and Electronic and Information Bioengineering at the University of Bari Medical School (Bachelor Degrees in Audiometric techniques, Audioprothesic techniques, Neurophysiopathology Techniques and Cardiocirculatory and Cardiovascular Perfusion Techniques).