1. Filippo Maria Bianchi
Address: 662 Davenport Rd., Toronto, Ontario, Canada
Phone: +1 647 8808746
email: filippombianchi@gmail.com
Work Experience
Feb 2014 - Current Visiting PhD at Ryerson University, Toronto
I am working in the Ubiquitous and Pervasive Computing Lab under the
supervision of Prof. Alireza Sadeghian from the department of Computer
Science. My primary work is in the development of novel multi-agent algo-
rithms related to the fields of knowledge and clusters discovery, automatic
image processing, classification and time-series forecasting with echo-state
networks.
Feb 2014 Technical Consultant at St. Micheal’s Hospital, Toronto
Research consultant through Ryerson University, development of automatic
fault-detection in surgery operations for St. Micheal’s hospital of Toronto.
Nov 2012 Collaboration with TELECOM Italia
Project designer of PDS (Personal Data Storage) features, involving analysis
of call data records aimed at profiling users, identifying anomalies in the calls
and at clustering users with similar features to develop result-based customer
phone plans.
Education
Oct 2015 PhD in Machine Learning and Computational Intelligence
Institution: Sapienza University, Rome.
Research Topics: Classification, Clustering, Intelligence systems, Graph and sequence
matching, Space embedding, Data driven learning methods, Data mining, Metric learning,
Knowledge discovery, Multi-Agent systems, Neural networking, Time-series analysis and
forecasting, Granular computing, Image processing, Time-Varying graphs, Evolutionary al-
gorithms, Pattern Recognition, Function approximation and Prediction problems.
Jul 2012 Masters Degree (Computer Engineering): Artificial Intelligence
and Robotics - Honours
Institution: Sapienza University, Rome
Thesis Topic: Design and implementation of a graph-embedding classification system.
Main Topics: Artificial Intelligence, Vision and Perception, Business models, Machine
Learning, Soft Computing, Computer Graphics, Robotics, Pattern Recognition, Data Man-
agement, Distributed Systems.
Mar 2009 Bachelor in Computer Engineering
Institution: Sapienza University, Rome
Thesis Topic: Design and implementation of an airport database in SQL.
Main Topics: Mathematics, Physics, Computer Programming Languages, Operative Sys-
tems, Networks Infrastructures, Economy, Telecommunications, Systems Theory, Databases,
Chemistry, Optimization, Electronics.
Languages
English, Italian.

2. Computer Skills
Advanced Knowledge: C, C++, Java, MATLAB, Windows, LATEX.
Intermediate Knowledge: SQL, mySQL, Assembly, Microsoft Office , Linux,
Multi-threading, GPU-Programming.
Basic Knowledge: Distributed Computing, OpenGL, DirectX.
Personal Interests
Technology, electronics, mathematics and robotics. Basic working knowledge of engines, elec-
trical, building and construction. Farming, rock climbing, cooking Italian cuisine.
Teaching
Teacher’s assistant during PhD facilitating seminars related to Machine Learning and Soft
Computing.
Supervision of several Computer Engineering Master’s students thesis work (2013 - current).
Publications
• F. M. Bianchi, L. Livi, A. Rizzi and A. Sadeghian - A Granular Computing approach to
the design of optimized graph classification systems - Springer, Soft Computing 2013.
• L. Livi, F. M. Bianchi, A. Rizzi and A. Sadeghian - Dissimilarity Space Embedding of
Labeled Graphs by a Clustering-based Compression Procedure - IJCNN 2013.
• F. M. Bianchi, L. Livi and A. Rizzi - Matching of Time-Varying Labeled Graphs - IJCNN
2013.
• F. M. Bianchi, L. Livi and A. Rizzi - Two Density-based k-means Initialization Algorithms
for Non-Metric Data Clustering – Springer, Pattern Analysis and Applications 2014.
• F. M. Bianchi, S. Scardapane, L. Livi, A. Uncini, and A. Rizzi – An Interpretable Graph-
based Image Classifier – WCCI 2014.
• F. M. Bianchi, S. Scardapane, A. Rizzi, A. Sadeghian - Automatic Classication and
Semantic Characterization of Images through Labeled Graphs - pending IEEE Access.
• F. M. Bianchi, E. Maiorino, L. Livi, A. Rizzi, A. Sadeghian - An Agent-Based Algorithm
exploiting Multiple Local Dissimilarities for Clusters Mining and Knowledge Discovery -
published on arXiv preprint 2015.