I am Simone Alghisi and I am a PhD Student in Information Engineering and Computer Science at the University of Trento, supervised by Prof. Giuseppe Riccardi. I have been selected as the 2nd candidate out of 58, with 93/100 points. I have been assigned a scholarship for a PhD in Area A: Deep and Structured Machine Learning, Machine Learning and Intelligent Optimization, Language Speech and Interaction.

I have earned my Master’s Degree in Artificial Intelligence Systems at the University of Trento in 2023 (110 with Honors). My Master’s thesis was titled Automatic and Semantic Detection of New Information in Document Time Series and was supervised by Prof. Giuseppe Riccardi, and co-supervised by Seyed Mahed Mousavi, PhD, and Gabriel Roccabruna.

I earned my Bachelor’s Degree in Computer Science at the University of Trento in 2021 (110 with Honors). My thesis was titled The Emotional Impact of Covid-19 and was supervised by Prof. Alberto Montresor, and co-supervised by Cristian Consonni, and David Laniado. This work is the result of my Erasmus+ traineeship period at Eurecat - Centre Tecnològic de Catalunya in Barcelona.

Passions

Usually, I enjoy spending time with my friends, always trying to involve them in any kind of activity, such as board game nights. I believe this aspect of my personality also reflects in my professional life, where I prefer taking a break in the company of someone, gladly exchanging a few words, rather than sipping my coffee alone.

I’m passionate about mountain hiking, and as for my hobbies, I’m a true enthusiast of Competitive Pokémon (specifically, VGC, no TCG, FYI). However, in reality, I actively participate only in mountain hiking, although I’ve tried to teach a model to play Pokémon (interesting but not fully satisfying due to resource constraints).

One of my big dreams would be to develop an artificial intelligence capable of acting as a “Master” in a Dungeons & Dragons game. This AI should be able to listen to the players’ ideas, manage in-game actions, and, at the same time, suggest new content (e.g., storytelling) based on them.