Matteo Cardellini

According to SCOPUS

Documents

8

Citations

32

h-index

3

Publications

2024

C10 - Taming Discretised PDDL+ through Multiple Discretisations - M. Cardellini, M. Maratea, F. Percassi, E. Scala and M. Vallati - Proceedings of the 34th International Conference on Automated Planning and Scheduling (ICAPS 2024)
C9 - Symbolic Numeric Planning with Patterns - M. Cardellini, E. Giunchiglia and M. Maratea - Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024)

2023

C8 - A Framework for Risk-Aware Routing of Connected Autonomous Vehicles via Artificial Intelligence - M. Cardellini, C. Dodaro, M. Maratea, M. Vallati - Proceedings of the 26th IEEE International Conference on Intelligent Transportation Systems (ITSC 2023)
J2 - Solving Rehabilitation Scheduling problems via a Two-Phase ASP approach - M. Cardellini, P. De Nardi, C. Dodaro, G. Galatà, A. Giardini, M. Maratea and I. Porro - Theory and Practice of Logic Programming, Volume 24, Issue 2, March 2024, pp. 344-367 (TPLP)
J1 - Rescheduling Rehabilitation Sessions with Answer Set Programming - M. Cardellini, C. Dodaro, G. Galatà, A. Giardini, M. Maratea, N. Nisopoli and I. Porro - Journal of Logic and Computation, Volume 33, Issue 4, June 2023, Pages 837–863 (JLC)

2022

C7 - An ASP Framework for Efficient Urban Traffic Optimization. - M. Cardellini - Electronic Proceedings of the 18th Doctoral Consortium on Logic Programming (ICLP DC 2022)

2021

C6 - A Two-Phase ASP Encoding for solving Rehabilitation Scheduling - M. Cardellini, P. De Nardi, C. Dodaro, G. Galatà, A. Giardini, M. Maratea and I. Porro - In Proceedings of the 5th International Joint Conference on Rules and Reasoning (RuleML+RR 2021)
T1 - Artificial Intelligence Techniques for Solving the In-Station Train Dispatching Problem - M. Cardellini - Master's Degree Thesis - 23/07/2021 - Università degli Studi di Genova
C5 - In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models - G. Boleto, L. Oneto, M. Cardellini, M. Maratea, M. Vallati, R. Canepa, D. Anguita - In Proceedings of the 29th European Symposium on Artificial Neural Networks (ESANN-21)
C4 - A Planning-based Approach for In-Station Train Dispatching - M. Cardellini, M. Maratea, M. Vallati, G. Boleto, L. Oneto - In Proceedings of the 14th Annual Symposium on Combinatorial Search (SoCS-21)
C3 - An Efficient Hybrid Planning Framework for In-Station Train Dispatching - M. Cardellini, M. Maratea, M. Vallati, G. Boleto, L. Oneto - In Proceedings of the International Conference on Computational Science (ICCS-21)
C2 - In-Station Train Dispatching: A PDDL+ Planning Approach - M. Cardellini, M. Maratea, M. Vallati, G. Boleto, L. Oneto - In Proceedings of the 31st International Conference on Automated Planning and Scheduling (ICAPS-21)

2020

C1 - Answer Set Programming in the Healthcare Domain: Extended Overview. - M. Alviano, R. Bertolucci, M. Cardellini, C. Dodaro, G. Galata, M. K. Khan, M. Maratea, M. Mochi, V. Morozan, I. Porro, M. Schouten - 19th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2020)

Education

National Ph.D. in Artificial Intelligence (PhD-AI.it)

Ph.D.
Politecnico di Torino
Università degli Studi di Genova
11/2021 - Current

The Italian National PhD Program in Artificial Intelligence is made of 5 federated PhD courses that bring together 61 universities and research institutions. The 5 PhD courses share a common basis in the foundations and developments of AI, and each one has an area of specialisation in a strategic sector of AI application. The area of Artificial Intelligence applied to Industry 4.0 is given to Politecnico di Torino

Scolarship: AI-based planning and scheduling for transportation systems

Artificial Intelligence is now becoming ubiquitous and an asset for many industrial sectors such as the one of transportation. New generation information systems collect and store large amounts of heterogeneous data, which allow Machine Learning algorithms to induce Data Driven models of complex physical systems. They scale well with the amount of data available, but they are not as effective if exploited for deduction purposes. On the contrary, Model Based Reasoning allows to model, in an effective way, such complex systems, based on the physical knowledge about them and deduce meaningful information by solving complex planning and scheduling optimization problems. Unfortunately, it is well known that they may not scale well with the size of problem. Therefore, a synergy between Machine Learning and Model Based Reasoning is required.

Relators: Prof. M. Maratea, Prof. E. Giunchiglia, Prof. M. Vallati

Computer Engineering - Artificial Intelligence and Human-Centered Computing

Master's Degree
Università degli Studi di Genova
09/2019 - 07/2021

Data Analysis and Data Mining, Computer Security, Operations Research, Human Computer Interaction, Software Engineering, Methods and Tools for Industrial Automation, Artificial Intelligence, Data Visualisation, Methods and Tools for Decision Support, Multimodal Systems, Embedded Systems, Semantic Web Technologies, Advanced Artificial Intelligence

Thesis: Artificial Intelligence Techniques for Solving the In-Station Train Dispatching Problem
Relators: Prof. M. Maratea, Prof. M. Vallati
Final Grade: 110/110 cum Laude and "Dignità di Stampa"

Computer Engineering

Bachelor's Degree
Università degli Studi di Genova
09/2016 - 09/2019

Mathematical Analysis, Information Technology, Digital Design, Geometry, General Physics, Circuits Theory, Electronic Computers, Databases, IT and Computing, Electrical Communications, Systems' Theory, Mathematical Physics, Design and Analysis of Algorithms, Electronic Devices and Circuits, Discrete Event Systems, Software Tools for Controls, Automatic Control, Web Application Development, Computer Networks

Thesis: Visual and Data Analytics for the analysis of train flows in the railway network
Relators: Prof. M. Maratea, Prof. L. Oneto
Final Grade: 110/110

Liceo Scientifico

High School
Convitto Nazionale C. Colombo
09/2010 - 06/2016

Mathematics, Physics, Latin, History, Philosophy, Art History, Italian, English

Final Grade: 90/100

Events

2024

ICAPS 2024 - 34th International Conference on Automated Planning and Scheduling PC Member
AAAI 2024 - 38th AAAI Conference on Artificial Intelligence - PC Member

2023

ECAI 2023 - 26th European Conference on Artificial Intelligence ECAI 2023 PC Member
ICAPS 2023 - The 33rd International Conference on Automated Planning and Scheduling PC Member
AAAI 2023 - 37th AAAI Conference on Artificial Intelligence - PC Member

2022

LPNMR 2022 - 16th International Conference on Logic Programming and Non-monotonic Reasoning - Local Commitee

Teaching Activities

Databases - Tutoring and Exercises - Prof. A. Boccalatte, Prof. M. Maratea - University of Genova (2022)
Advanced Artificial Intelligence. Invited talks on applications of Planning and Scheduling techniques for real world domains. Prof. M. Maratea - University of Genova. (2020, 2021, 2022)

Supervisor Activities

2022

S2 - A. Formica - Master's Degree in Computer Engineering (October 2022) - In-Station Train Dispatching via Artificial Intelligence Techniques: Optimisation, Rescheduling and Visualisation - Co-supervisor with Prof. M. Maratea
S1 C. Ansaldo, N. Chiesa - Bachelor's Degree in Computer Engineering (July 2022) - - Tecniche di Intelligenza Artificiale per la Risoluzione del Problema di Pianificazione Turni - Co-supervisor with Prof. M. Maratea

Awards

Award AIxIA Leonardo Lesmo 2022. Special mention for the best Italian Master’s Degree Thesis in Artificial Intelligence (link)

Work Experiences

SurgiQ SRL

Genoa, Italy
Researcher
04/2021 - 10/2021
Answer Set Programming
NodeJS Matlab

Built and optimized scheduling systems based on state-of-the-art artificial intelligence’s technologies for the scheduling of physiotherapic sessions for the rehabilitation of patients in hospitals.

Secondhand Mobile SRL

Genoa, Italy
CTO & Co-founder
02/2018 - 03/2021
AngularJS HTML LESS
Cordova/Ionic NodeJS
Built a cloud based management system using Angular, NodeJS and AWS accessed daily by more than 140 customers all-over Italy.
Built and published an iOS/Android App with 65k active downloads.
Helped the company to grow to 14 employees and a yearly revenue of 5 million euros.
Managed 4 software engineers using an Agile methodology continuously delivering improvements to the corporate code-base.

SmileApp

Genoa, Italy
Freelance Developer
02/2015 - 02/2018
AngularJS HTML LESS
Cordova/Ionic NodeJS

As soon as I turned 18 I started my own freelancer activity, SmileApp, building mobile applications and websites for stores and companies in my hometown, Genoa. In my portfolio I have many clients, among which stand out an important phone reseller, Stylecar, with over six thousand clients registered in the application that I built, and a medical and dentistry conference organiser, e20, with more than forty thousand clients all over Italy.

Sablono GmbH

Berlin, Germany
Front End Developer, Intern
07/2016 - 09/2016
NodeJS Socket.io

My amazing experience at Sablono and the awesome people that I met during the previous summer were the reason I decided to come back in the summer of 2016 to work again at Sablono. This time, besides building the Sablono platform, I also lead some side projects, that has been later implemented in the main workflow, implementating a live communication between the web platform and the mobile application using NodeJS and Socket.io and a system of push notifications through APNs and GCM.

Sablono GmbH

Berlin, Germany
Front End Developer, Intern
06/2015 - 09/2015
AngularJS HTML LESS Ionic

Sablono is an IT Company based in Berlin which provides a web application for construction companies to easily track their progress across multiple construction sites. My work was to build clear and efficient user interfaces for the web application employing AngularJS as the main framework. This experience made me really understand the working environment and how big teams operate together to achieve a common goal through methods like Git for the versioning and publishing control and the Agile Method Scrum for managing the product development.