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Hello, my name isand in December 2023 I got my Ph.D. in Computer Science under the supervision of Gabriele Bavota. I'm a Data Scientist at the Università della Svizzera Italiana in Lugano. I'm part of the STAR research group led by Mauro Pezzè.
Education and Professional Experience
Education
PhD in Computer Science
May 2020 - December 2023
Università della Svizzera Italiana, Lugano
My Ph.D. research is centered on leveraging Machine and Deep Learning models to facilitate the automatic generation of text. Throughout my research papers, I conducted Generative AI experiments with various cutting-edge models such as T5, CodeT5, RoBERTa, and GitHub Copilot.
Master in High Apprenticeship in Analytics and Business Intelligence
July 2015 - July 2017
Polytechnic of Milan, Milan
During my Master's, I extensively delved into Big Data and Machine Learning topics. Additionally, I developed a tool utilizing NoSQL databases (MongoDB) and a NodeJS architecture integrated with Angular to solve Machine Learning tasks.
Master Degree in Mathematical Engineering, Statistical Address
October 2012 - April 2015
Polytechnic of Milan, Milan
During these years, I studied statistics at 360 degrees, enriching my knowledge with Optimization, Data Analysis and Programming courses.
Bachelor's Degree in Mathematical Engineering
September 2009 - September 2012
Polytechnic of Milan, Milan
During my Bachelor's Degree, I studied Mathematical Analysis, Statistics, Computer Science, Physics and Probability.
Professional Experience
Data Scientist
January 2024 - Present
Università della Svizzera Italiana, Lugano
'm participating in Machine Learning projects, leading a team of three people and overseeing their activities to ensure the successful and timely completion of the ongoing projects.
Data Scientist @ Machine Learning Center Of Excellence
March 2019 - April 2020
Accenture S.p.A., Milan
I realized different tools for Computer Vision and Natural Language Processing released in portable services, using Flask with HTML and CSS. Orchestrated the deployment of Docker containers exposing a Node.js server, integrating AI into home appliances and enabling the vocal interaction between users and a washing machine.
.NET Developer
October 2017 - February 2019
Aglea S.r.L., Milan
Realization of internal tools in C# and study of authorization security in SAP. Production of a tool to manage activities in my company (purchasing, invoicing, ..) based on a SQL database.
Business Intelligence Consultant
January 2015 - September 2017
NextInt S.a.s., Milan
I developed Dashboards and Reports using QlikView. I also implemented Machine and Deep Learning projects using Python, Rapidminer, and R Studio, to help customers leverage their corporate data for informed decision-making.
Publications
The Trailer of the ACM 2030 Roadmap for Software Engineering
M Pezzè, M. Ciniselli, L. di Grazia, N. Puccinelli, K. Qui
ACM SIGSOFT Software Engineering Notes
From Today's Code to Tomorrow's Symphony: The AI Transformation of Developer's Routine by 2030
M. Ciniselli, N. Puccinelli, K. Qiu, L. Di Grazia
Foundation of Software Engineering (FSE 2024 Special Issue)
On the Generalizability of Deep Learning-based Code Completion Across Programming Language Versions
M. Ciniselli, A. Martin-Lopez, G. Bavota
International Conference on Programming Comprehension (ICPC 2024)
Towards Summarizing Code Snippets Using Pre-Trained Transformers
A. Mastropaolo, M. Ciniselli, L. Pascarella, R. Tufano, E. Aghajani, G. Bavota
International Conference on Programming Comprehension (ICPC 2024)
Evaluating Code Summarization Techniques: A New Metric and an Empirical Characterization
A. Mastropaolo, M. Ciniselli, M. di Penta, G. Bavota
International Conference on Software Engineering (ICSE 2024)
Code Review Automation: Strengths and Weaknesses of the State of the Art
R. Tufano, O. Dabić, A. Mastropaolo, M. Ciniselli, G. Bavota
IEEE Transactions on Software Engineering (TSE 2024), 16 pages
On the robustness of code generation techniques: An empirical study on github copilot
A Mastropaolo, L Pascarella, E Guglielmi, M. Ciniselli, S Scalabrino, R Oliveto, G Bavota
International Conference on Software Engineering (ICSE 2023)
Source Code Recommender Systems: The Practitioners' Perspective
M. Ciniselli, L. Pascarella, E Aghajani, S Scalabrino, R Oliveto, G Bavota
International Conference on Software Engineering (ICSE 2023), to appear
To What Extent do Deep Learning-based Code Recommenders Generate Predictions by Cloning Code from the Training Set?
M. Ciniselli, L. Pascarella, G. Bavota
Mining Software Repositories (MSR 2022), 12 pages
An Empirical Study on the Usage of Transformer Models for Code Completion
M. Ciniselli, N. Cooper, L. Pascarella, A.Mastropaolo, E. Aghajani, D. Poshyvanyk, M. Di Penta, G. Bavota
IEEE Transactions on Software Engineering (TSE 2021), 20 pages
An Empirical Study on the Usage of BERT Models for Code Completion
M. Ciniselli, N. Cooper, L. Pascarella, D. Poshyvanyk, M. Di Penta, G. Bavota
Mining Software Repositories (MSR 2021), 12 pages