Andrea Galassi Home Page

Andrea Galassi Home Page Wed, 07/03/2018 - 15:19


Andrea Galassi

3rd year PhD student

DISI, Università di Bologna
Viale del Risorgimento 2, 40136 - Bologna (IT)

email: a<dot>galassi<at>unibo<dot>it


I am a second year PhD student at the Computer Science and Engineer department (DISI) of the University of Bologna. My supervisor is Professor Paolo Torroni.

My PhD is focused on the application of Artificial Intelligence and Machine Learning techniques to Argumentation Mining and similar Natural Language Processing tasks.

My research interests involve also the investigation of what Deep Networks can achieve by themselves and possible ways to combine symbolic and sub-symbolic techniques. So far, we have conducted our investigation on board games and Constraint Satisfaction Problems.

I've been teaching assistant ("Tutor Didattico") of professors Paola Mello, Federico Chesani, and Paolo Torroni. I am one of the responsible of the Board Game Students Challenge. I am also co-supervisor in some bachelor thesis, masters thesis, and course projects, most of them regarding machine learning application.

I have visited Stanford University during summer 2018, working under the supervision of Margaret Hagan in the context of the MIREL project.


Recent works and news:


Projects in which I am or I've been involved:

  • Claudette: Machine Learning Powered Analysis of Consumer Contracts and Privacy Policies
  • Argumentation Mining: extraction of arguments from unstructured textual documents
  • Games and AI: application of Artificial Intelligence techniques in the context of games
  • Habitat: Home Assistance Based on the Internet of Things for the AuTonomy
  • DeepOpt



Teaching Sun, 06/10/2019 - 00:24

I am currently covering the role of teaching assistant for the following courses:

"Languages and Algorithms for Artificial Intelligence", prof. Paolo Torroni.

"Natural Language Processing", prof. Maurizio Gabbrielli.


In the past, I have covered the role of teaching assistant for the following courses:

"Real Time OS M - Real Time Systems for Automation M", Prof. Paolo Torroni, material on the website:

"Fondamenti di Informatica T1", Prof. Paola Mello e Federico Chesani, material on the website:


Lectures Material

Natural Language Processing and Learning (Bologna, 12/04/2019, as part of the Intelligent Systems M course of Prof. Michela Milano)


Thesis and project activities topics

I also supervise bachelor thesis, master thesis and project activities.

Possible topics are listed here, others may be available in the AI course website:


  • Neural networks applied to games: application of neural networks and deep networks for the solution of board games and (small/simple) video games.
  • Solving/find the complexity of a board game: make use of AI technique to compute the complexity of a board game or to solve it (to a certain degree)
  • Natural Language Processing: projects and thesis on argumentation mining (finding the discussion inside a text), sentiment analysis (finding the "sentiment" in a text), fake news identification (from text), cyberbullying identification (from text)
  • Deep networks for CSPs: application and analysis of deep networks for the solution of constrained problems.

Specific projects:

  • Creation of a Keyforge AI player: design and implement an AI to play the game Keyforge card game. A possible implementation of the game can be found here:
  • Creation of predictor for Keyforge match outcome: create an AI module capable of predicting the outcome of a Keyforge game. An existing dataset of games can be used for evaluation (and for training in case of machine learning approaches).
  • Creation of a Keyforge deck evaluation: create a machine-learning based system capable of automatically score a deck of Keyforge according to popular metrics (for example, SAS and AERC, but other suggestions are welcomed)


Past activities

Some of the activities I have supervised are the following:

  • Mihail Bida, Francesco Pandol, "Framework per giocare ad Hanabi e implementazione di diverse strategie di gioco", 2020. Code repository.
  • Andrea Conti, project activity, "Deep Q-Learning applicato a Super Mario Bros", 2019. Code repository.
  • Francesco Giovanelli, master thesis, "Model Agnostic solution of CSPs with Deep Learning", 2019. Code repository.
  • Giacomo Pinardi, bachelor thesis, "Apprendimento supervisionato di un gioco da tavolo asimmetrico tramite reti neurali: un caso di studio su Tablut", 2019
  • Alessio Leurini, bachelor thesis, "Cross-Domain Sentiment Analysis", 2019
  • Alessandro Ravaglia, bachelor thesis, "Studio delle tecniche di reinforcement learning e delle loro applicazioni ai giochi da tavolo", 2019
  • Guardati Simone, project activity, "Applicazione di tecniche di Machine Learning al gioco Mastermind", 2019
  • Andrea Piretti, bachelor thesis, "Sviluppo di un'architettura software distribuita con supporto a giocatori artificiali: il caso di studio del gioco da tavolo Tablut", 2018
  • Nicola Alessi, project activity, 2018
  • Grilli Matteo, bachelor thesis, "Reti neurali profonde applicate a giochi di carte digitali: un caso di studio su Hearthstone semplificato", 2017

Publications and Research Material

Publications and Research Material Wed, 13/02/2019 - 16:35


2020, COLINGCross-lingual Annotation Projection in Legal Texts

2020, IEEE Transactions on Neural Networks and Learning SystemsAttention in Natural Language Processing

2020, Frontiers on Big DataNeural-Symbolic Argumentation Mining: an Argument in Favor of Deep Learning and Reasoning

2018, 5th Workshop on Argument MiningArgumentative Link Prediction using Residual Networks and Multi-Objective Learning


Deep Networks and CSPs

2018, CPAIORModel agnostic solution of CSPs via Deep Learning: a preliminary study


2019, technical report: An Upper Bound on the Complexity of Tablut

2018, IEEE Transactions on GamesCan Deep Networks Learn to Play by the Rules? A Case Study on Nine Men’s Morris



2017, AI*IAA Game-Based Competition as Instrument for Teaching Artificial Intelligence



2019, Sensors: HABITAT: An IoT solution for independent elderly

A Game-Based Competition as Instrument for Teaching Artificial Intelligence

A Game-Based Competition as Instrument for Teaching Artificial Intelligence Sat, 11/11/2017 - 13:31

Publicly Accessible Resources

Argumentative Link Prediction using Residual Networks and Multi-Objective Learning

Argumentative Link Prediction using Residual Networks and Multi-Objective Learning Wed, 31/10/2018 - 10:26

Publicly Accessible Resources