You can find my complete by following this link: CURRICULUM VITAE.
Education and Research Experiences
|October 2015 – Today||Postdoctoral Researcher, Vrije Universiteit Brussel, Belgium.
Main Research Topic: Behaviour Understanding, Intelligent Surveillance, Robotic Vision, Human Robot Interaction.
Principal Investigator for the project COACHES.
|November 2014 – August 2015||Postdoctoral Researcher, Sapienza University of Rome, Italy.
Main Research Topic: Behaviour Understanding, Intelligent Surveillance, Medical Imaging, Robotic Vision.
|October 2011 – October 2014||Ph.D. Student in Engineering in Computer Science, Sapienza University of Rome, Italy.
Thesis: Automatic Surveillance with Multiple-Sensor Network.
The problem of monitoring people in a wide area is an open research challenge. Automatic surveillance of wide areas requires the capacity of detecting and recognizing possible abnormal situations in populated environments. In general, a critical infrastructure (CI) is an asset which is essential for the maintenance of vital societal functions. Public areas, such as airports, train stations, shopping malls, and offices, are examples of CIs that can be a target for terrorist attacks, criminal activities or malicious behaviors. Tragic events in the last decade have enhanced the focus on safety of people, assets and public places. Many video surveillance systems based on a multitude of cameras have been set up for monitoring public areas and the output of these cameras is fed into a set of monitors. However, traditional passive video surveillance is ineffective when the number of cameras exceeds the ability of human operators to keep track of the evolving scene and the possibility of making errors increases exponentially over time.
This thesis presents a framework for human behavior understanding with multiple heterogeneous sensors, conceived for providing guidance through the design and implementation of real-world intelligent surveillance systems. The main contributions of the thesis are:
• A formal characterization of two views of a general multi-sensor frame- work for human behavior understanding, including input and output data formats;
• The design, implementation, and experimental evaluation of different sys- tems that combine heterogeneous sensors;
• The descriptions of two different real system architectures;
• An extensive experimental evaluation for the proposed solutions;
• A novel algorithm for RGB image segmentation;
• An unsupervised approach for human crowd behavior understanding;
• A multi-sensor approach for indoor surveillance.
In this thesis, the main state-of-the-art modular architectures for automatic surveillance are described and different solutions for improving each module performance are proposed. Quantitative evaluation metrics as well as experi- mental results for the proposed solutions are shown and future directions are discussed.
|May 2013 – October 2013||Visiting Student Robot Vision Team (RoViT), Faculty of Computing, Information Systems and Mathematics (CISM), Kingston University, London|
|October 2010 – October 2011||Research Assistant, Sapienza University of Rome. My Principal topic was to analyse a bus stop for determining a roughly number of people present in the scene.|
|May 2014||Starting Research Grant. Sapienza University of Rome, Italy.
I won an Athenaeum Grant for a research proposal on Medical Image Analysis. Link: Progetti Avvio Ricerca
|May 2013||6 months Fellowship. Sapienza University of Rome, Italy.
|October 2011||Three Years Fellowship. Sapienza University of Rome, Italy.
|July 2012||I participated with success at International Computer Vision Summer School (ICVSS).|
|May 2011||I participated at First Short Spring School on Surveillance.|
|January 2015 – Today||Computer Vision and Image Understanding.|
|February 2015 – Today||International Journal of Computational Vision and Robotics.|
|December 2014 – Today||IET Image Processing.|