MSc Computer Engineering | University of Bologna | 09/2020 - Present | GPA: 29.9/30

  • Fellow at the Collegio Superiore, the honors program of the University of Bologna, offering additional advanced and interdisciplinary education. Admission is solely based on merit. Students are provided exemption from annual fees, free accommodation, an annual scholarship and the tutorship of a distinguished professor, in my case prof. Paolo Torroni, throughout their bachelor’s and MSc degrees. Admission rate: <5%.
  • Consolidated quantitative skills taking courses in operations research and mathematical optimization, search-, learning-, and planning-based artificial intelligence, game theory and viability of business projects. Attended additional courses about mathematical methods for artificial intelligence as well as equality and efficiency in taxation policies at Collegio Superiore.
  • Erasmus+ exchange at the Universitat Politècnica de Catalunya, Barcelona, for first semester of the the second year. Enrolled in the Data Science track of the MSc in Innovation and Research in Informatics, with a study plan focused on machine learning and mathematical optimization.
  • Exchange at the École Normale Supérieure, Paris, for the second semester of the second year. Enrolled in the Economics department and attending courses from the MSc in Analysis and Policy in Economics of the Paris School of Economics.

BSc Computer Engineering | University of Bologna | 09/2017 - 07/2020 | Summa Cum Laude (110L/110), GPA: 29.6/30

  • Thesis: “Machine Learning for Semantic Visual SLAM”, supervisors: prof. Stefano Mattoccia (University of Bologna) and prof. Stefano Stramigioli (University of Twente). Tutor at Collegio Superiore: prof. Elena Zattoni.
  • Strongly quantitative study plan, taking courses in advanced multivariate calculus, numerical analysis, C++11/14, Java, R, Go, Matlab and Python programming, statistical modeling, SQL and data engineering, economics and business organization. Attended additional courses in game theory, blockchain design and optimal control in economics at Collegio Superiore.

Work experience

Research Assistant | Paris School of Economics, France | 10/2021 - Present

  • Project work financed by the French Ministry of Labor, with the goal of using natural language processing to construct reliable measures of occupation-to-occupation skill distances.
  • Data from this research project is to be used by the Ministry to guide the design of public policies aimed at re-training workers from distressed occupations, in order to maximize their re-employment chances.
  • Working on a dataset of actual job-to-job and unemployment-to-job mobilities as well as the “classification ROME des métiers”, the French occupation classification.

Research Intern | Robotics and Mechatronics, University of Twente, Netherlands | 03/2020 - 06/2020

  • Erasmus+ traineeship under the supervision of prof. Stefano Stramigioli (University of Twente) with the goal of improving the localization and mapping (SLAM) capabilities of an unmanned aerial vehicle through research and deployment of deep neural networks for semantic segmentation of 3D scenes.
  • Developed a module for the ROS framework making use of TensorFlow’s, TensorFlow Lite’s and PyTorch’s C++ and Python APIs.
  • The end goal of the project was the development of an autonomous vehicle that can efficiently interact with the surrounding environment, for example to aid or replace humans in high-risk situations such as dangerous maintenance work.

Projects, honors and awards

  • Selected to attend the Cornell, Maryland, Max Planck Pre-doctoral Research School 2021, a summer school aimed at top students in computer science interested in pursuing a PhD track.
  • As a student in Collegio Superiore, every year I write 5 papers based on individual research on topics addressed during the courses. Selected titles include “What can economsts learn from machine learning?” (published 2020), “Computer science and engineering tools for resource economics”, “The platformization of the Internet infrastructure: economic and social effects in cities”.
  • Led a team of 4 people to develop an artificial intelligence able to play the Nordic board game Tablut using informed tree search techniques, training metaparameters with a genetic algorithm. Project completed in spring 2021.
  • Developed a parallelized implementation of the Q-learning algorithm leveraging Xilinx FPGA hardware using high-level synthesis tools. Project completed in spring 2021.
  • Game engine pathfinder: developed a pathfinding solution in fall 2019 that is able to efficiently find optimal and collision-free paths for an arbitrary number of actors in an open source game engine developed in C++11 and Python 3
  • Italian national selection for the International Olympiad in Informatics (IOI): bronze medal won in the 2016 final round of individual competitions, third place in the 2016 final round of team competitions.

Teaching activities

  • Course in Argumentation in Artificial Intelligence. Teaching Assistant to prof. Paolo Torroni, University of Bologna, fall 2021
  • BSc course in Software Engineering. Teaching Assistant to prof. Marco Patella, University of Bologna, 2021
  • High school course in Competitive Programming. Teacher, Istituto Tecnico Aldini Valeriani, Bologna, 2020-2021
  • High school course in Computer Science. Teacher, Istituto Tecnico Aldini Valeriani, Bologna, 2020-2021


Frick, K. M. What can economists learn from machine learning? in Astrazioni stenografiche. Concetti chiave per vivere consapevolmente la nostra società (Bononia University Press, 2020).