Elena Carlotta Olivetti

Elena Carlotta Olivetti is a Fixed-term Assistant Professor at the Department of Management and Production Engineering (DIGEP) at Polytechnic University of Turin. She serves as an invited member of the College of Biomedical Engineering and the College of Chemical and Materials Engineering.

Her educational background includes a Master's degree in Biomedical Engineering, and she is currently pursuing a PhD in Management, Production, and Design at the same institution.

Dr. Olivetti's research focuses on the intersection of 3D graphics, biometrics, and medical applications. Her work primarily centers on 3D face analysis for medical applications, particularly in maxillofacial surgery. She applies machine learning techniques, including Deep Convolutional Neural Networks, to develop innovative solutions for facial recognition and prediction of surgical outcomes. Her research spans across virtual reality environments for stress assessment, biometric applications, and 3D modeling for medical diagnostics and surgery planning.

Her recent publications demonstrate a strong trend toward interdisciplinary research combining computer science, neuroscience, and medical applications. She has made significant contributions to the field of 3D facial prediction for orthognathic surgeries and affective computing using EEG and machine learning in VR environments. Her work bridges the gap between engineering and medical sciences, creating practical applications for healthcare professionals.

Dr. Olivetti serves as a PhD supervisor for Francesca Giada Antonaci in the Bioengineering and Medical-Surgical Sciences program. She is actively involved in teaching both at the Master's level (3D graphics solutions in biometric applications for Biomedical Engineering) and Bachelor's level (Industrial Technical Drawing for Chemical and Food Engineering).

As a key member of the 3D LAB Research Group, she contributes to projects focused on human-computer interaction, 3D data acquisition and visualization, facial morphology analysis, and augmented reality applications in medical contexts. The lab works on developing innovative solutions for diagnostics, surgery planning, and medical software applications.