Andrea Generosi

Position

Research fellow - ING-IND/15

Tutor

Prof. Maura Mengoni

Research Areas

His research activity concerns the development of Deep Learning technologies to analyze a user or customer in digital or physical contexts, so to extrapolate KPIs concerning their User and Customer Experience. The study focuses mainly on the design and implementation of technologies for the automatic recognition of emotions, gender, age and gaze from photos and / or video of the analyzed user’s face, mainly using the training of Convolutional Neural Networks.

Capsule Bio

Andrea Generosi obtained his master's degree in Computer and Automation Engineering in February 2016 at the Polytechnic University of Marche and suddenly began working as an ICT consultant at the Italian headquarters of the Hewlett Packard Enterprise company in Cernusco sul Naviglio (MI). In November of the same year he began his PhD in Industrial Engineering at the Polytechnic University of Marche and contributed to found, in February 2017, the university spin-off Emoj, of which he is now the CTO.

Publications
  1. Ceccacci, S., Generosi, A., Giraldi, L., Mengoni, M. (Sep 2017) An User-Centered approach to design Smart Systems for people with dementia. ICCE-BERLIN 2017.
  2. Ceccacci, S., Generosi, A., Giraldi, L., Mengoni, M. (May 2018) Tool to Make Shopping Experience Responsive to Customer Emotions. INTERNATIONAL JOURNAL OF AUTOMATION TECHNOLOGY.
  3. Generosi, A., Ceccacci, S., Mengoni, M. (2018) A deep learning-based system to track and analyze customer behavior in retail store. ICCE-BERLIN 2018
  4. Generosi, A., Altieri, A., Ceccacci, S., Foresi, G., Talipu, A., Turri, G., Mengoni, M. (2019) MoBeTrack: A Toolkit to Analyze User Experience of Mobile Apps in the Wild. ICCE 2019
  5. Altieri, A., Ceccacci, S., Ciabattoni, L., Generosi, A., Talipu, A., Turri, G., Mengoni, M. (2019) An Adaptive System to Manage Playlists and Lighting Scenarios Based on the User's Emotions. ICCE 2019
 

Email:
a.generosi@staff.univpm.it

Phone:
+39 071 220 4797

Office:
Q180_017

         Research Gate