Viviana Pentangelo

Ph.D. Student in Computer Science

About me

About me

Hello! 👋 I am Viviana Pentangelo, a Ph.D. student in Computer Science at University of Salerno, advised by Prof. Fabio Palomba.

In 2018, I enrolled in the Computer Science course at the University of Salerno without knowing how to write a single line of code. During those years, I began to explore this vast world and developed a particular interest in Software Engineering, Computer Graphics, and Machine Learning. This led to the attainment of my Bachelor's Degree (magna cum laude) in 2021, defending a thesis on the Automated Generation of 3D Human Models.

Right after, I enrolled in the Master's program in Computer Science, curriculum of Data Science and Machine Learning, where I deepened my interests and started delving into the emerging context of the Metaverse. In 2023, I completed my Master's Degree (magna cum laude), defending a thesis regarding the Development and Evaluation of an Engineered Educational Metaverse.

Currently, I have embarked on my journey as a Ph.D. student in Computer Science, focusing on Metaverse Engineering, Metaverse for E-Health, and Machine Learning techniques for the generation of 3D environments.

Personal Information

  • Birthday: May 2000
  • Location: Salerno (SA) - Italy
  • Nationality: Italian
  • University: University of Salerno, Fisciano (SA) - Italy
  • Department: Computer Science
  • Research Group: SeSa Lab, Via Giovanni Paolo II, 123 Fisciano (SA) - Italy


Philosophiae Doctor

November 2023 - Current

University of Salerno | Salerno (SA) - Italy

Ph.D. course in Computer Science, curriculum of Computer Science and Information Technology, at SeSa Lab

Master's Degree

September 2021 - September 2023

University of Salerno | Salerno (SA) - Italy

Master's Degree in Computer Science, curriculum of Data Science and Machine Learning

- Finale grade: 110/110 cum laude

- Thesis title: The Metaverse Classroom: Development and Evaluation of an Engineered Educational Metaverse

- Supervisor: Prof. Fabio Palomba

Bachelor's Degree

September 2018 - September 2021

University of Salerno | Salerno (SA) - Italy

Bachelor's Degree in Computer Science

- Finale grade: 110/110 cum laude

- Thesis title: Automated Generation of 3D Human Models for Virtual Fitting

- Supervisors: Prof. Andrea F. Abate, Dr. Ignazio Passero



SENEM: A Software Engineering-Enabled Educational Metaverse

V. Pentangelo, D. Di Dario, S. Lambiase, F. Ferrucci, C. Gravino, F. Palomba

Elsevier's Journal of Information and Software Technology (IST), 2024

Context: The term metaverse refers to a persistent, virtual, three-dimensional environment where individuals may communicate, engage, and collaborate. One of the most multifaceted and challenging use cases of the metaverse is education, where educators and learners may require multiple technical, social, psychological, and interaction instruments to accomplish their learning objectives. While the characteristics of the metaverse might nicely fit the problem’s needs, our research points out a noticeable lack of knowledge into (1) the specific requirements that an educational metaverse should actually fulfill to let educators and learners successfully interact towards their objectives and (2) how to design an appropriate educational metaverse for both educators and learners.
Objective: In this paper, we aim to bridge this knowledge gap by proposing SENEM, a novel software engineering-enabled educational metaverse. We first elicit a set of functional requirements that an educational metaverse should fulfill.
Method: In this respect, we conduct a literature survey to extract the currently available knowledge on the matter discussed by the research community, and afterward, we assess and complement such knowledge through semi-structured interviews with educators and learners. Upon completing the requirements elicitation stage, we then build our prototype implementation of SENEM, a metaverse that makes available to educators and learners the features identified in the previous stage. Finally, we evaluate the tool in terms of learnability, efficiency, and satisfaction through a Rapid Iterative Testing and Evaluation research approach, leading us to the iterative refinement of our prototype.
Results: Through our survey strategy, we extracted nine requirements that guided the tool development that the study participants positively evaluated.
Conclusion: Our study reveals that the target audience appreciates the elicited design strategy. Our work has the potential to form a solid contribution that other researchers can use as a basis for further improvements.

Collecting and Implementing Ethical Guidelines for Emotion Recognition in an Educational Metaverse

D. Di Dario, V. Pentangelo, M. I. Colella, F. Palomba, C. Gravino

Proceedings of the 1st International Workshop on User-Centered Practices of Knowledge Discovery in Educational Data (UKDE 2024)

The metaverse represents a persistent, online 3D universe where people can interact, socialize, and work toward common goals. Education represents a key application domain, as it has the potential to enhance experiential learning and collaboration between learners and between learners and educators. However, challenges to the widespread adoption of educational metaverses persist. This paper focuses on emotional isolation, i.e., the feeling of emotional disconnection or loneliness, which can hinder learners’ motivation and participation. Machine learning-enabled emotional recognition systems have the potential to address this challenge, offering educators with feedback on the emotional states of learners within the metaverse. Yet, the integration of emotion recognition systems raises ethical concerns regarding consent, privacy, and algorithmic bias. In this paper, we first conduct a literature review on the ethical considerations surrounding the deployment of emotion recognition technology within educational metaverses. Then, we report on the implementation of these guidelines within SENEM, an educational metaverse platform available in the literature. Through this research, we aim to contribute to the responsible deployment of emotion recognition technology in educational settings, ultimately fostering a supportive and inclusive learning environment for all learners.

Breaking Barriers in the Metaverse: A Comprehensive Exploration of Accessibility for Users with Disabilities

D. Di Dario, G. Sellitto, V. Pentangelo, M. L. Fede, F. Ferrucci

Proceedings of the 1st Workshop on Artificial Intelligence with and for Learning Sciences (WAILS 2024)

In the post-pandemic era, more and more people are turning to virtual spaces for entertainment, work, education, and social interaction. Despite this enthusiasm, serious concerns have arisen regarding the accessibility and inclusion of people with disabilities in educational settings and how Artificial Intelligence (AI) approaches can mitigate these issues in the new digital realm. In this article, we conduct a systematic literature review (SRL) to identify the set of challenges that people and students with disabilities encounter when they are interested in accessing the metaverse. We collect solutions proposed in the literature to provide a comprehensive understanding of the accessibility of current metaverse platforms. We distill a number of takeaway messages encouraging researchers and practitioners to further work on the proposed solution, leveraging AI to monitor and enable people with disabilities to fully enjoy the metaverse experience.

Community Smell Detection and Refactoring in SLACK: The CADOCS Project

G. Voria, V. Pentangelo, A. Della Porta, S. Lambiase, G. Catolino, F. Palomba, F. Ferrucci

Proceedings of the 38th IEEE International Conference on Software Maintenance and Evolution (ICSME Tool Demo Track 2022)

Software engineering is a human-centered activity involving various stakeholders with different backgrounds that have to communicate and collaborate to reach shared objectives. The emergence of conflicts among stakeholders may lead to undesired effects on software maintainability, yet it is often unavoidable in the long run. Community smells, i.e., sub-optimal communication and collaboration practices, have been defined to map recurrent conflicts among developers. While some community smell detection tools have been proposed in the recent past, these can be mainly used for research purposes because of their limited level of usability and user engagement. To facilitate a wider use of community smell-related information by practitioners, we present CADOCS, a client-server conversational agent that builds on top of a previous community smell detection tool proposed by Almarini et al. to (1) make it usable within a well-established communication channel like Slack and (2) augment it by providing initial support to software analytics instruments useful to diagnose and refactor community smells. We describe the features of the tool and the preliminary evaluation conducted to assess and improve robustness and usability.
Academic Projects

Academic Projects

Some of the projects I have participated in developed within the academic context

  • All
  • Machine Learning
  • Computer Graphics
  • Unity3D
  • Tool
  • Web

The Metaverse Classroom

A collaborative 3D virtual environment for academic and educational purposes developed with Unity3D

3D Human Body Generator

A web tool to create a fully customizable 3D human body with given the body measurements


A conversational agent for the detection of community smells

AI Plays Tetris

An Unity3D and ML-Agents project with neural network trained by reinforcement learning that plays the Tetris game

ASL Alphabet Recognition

A Convolutional Neural Network that can recognize the ASL Alphabet live with a webcam


A Spring Boot web application for library support

Professional Service

Professional Service

Teaching Activities

Teaching Assistant for Fundamentals of Artificial Intelligence

Course from the Bachelor's Degree of Computer Science at University of Salerno (Prof. Fabio Palomba)

30 hours of Help Teaching for the Fundamentals of Artificial Intelligence course

Talks & Seminars

Talk @ SATToSE 2023

15th Seminar on Advanced Techniques & Tools for Software Evolution (SATToSE) at 16th International Summer School on Software Engineering (ISSSE 2023)

Presentation titled "Conversational Agents for the Detection Of Community Smells: The CADOCS Project"


Multimedia Tools & Applications Journal

Reviewer for the Multimedia Tools & Applications International Journal

Reviewer for the Multimedia Tools & Applications Special Issue: Metaverse and E-Learning Platforms



How to reach me


Via Giovanni Paolo II, 123 Fisciano (SA) - Italy