Mirco Musolesi
Biographic Data
| ID | 7717879 |
|---|---|
| NAME | Mirco Musolesi |
| GIVEN NAMES | Mirco |
| FAMILY NAME | Musolesi |
| SIGNATURE | MUSOLESI M |
| AFFILIATIONS | University College London |
| ORCID | 0000-0001-9712-4090 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Tracking the Temporal Evolution of Online Social Relationships in Times of Crisis
Social scientists have conceptualised different dimensions of human relationships, including knowledge, identity, and social support. At times of crisis, such as during a pandemic, social relationships can be disrupted, affecting the nature of interactions individuals have with others within their community and beyond. Understanding how relationships change, in both structure and content, can reveal how communities adapt and which connections are…
“What are they not telling me?” Learning machine learning
Machine Learning (ML) is increasingly accessible to users with limited knowledge of its theoretical foundations. However, misapplying it can lead to negative consequences. This paper reports on a qualitative study designed to reveal challenges that novices encounter when learning about basic ML concepts and building their first models. Twenty participants were introduced to fundamental ML concepts for classification through an interactive tutoria…
On the creativity of large language models
Large language models (LLMs) are revolutionizing several areas of Artificial Intelligence. One of the most remarkable applications is creative writing, e.g., poetry or storytelling: the generated outputs are often of astonishing quality. However, a natural question arises: can LLMs be really considered creative? In this article, we first analyze the development of LLMs under the lens of creativity theories, investigating the key open questions an…
The role of space, time and sociability in predicting social encounters
Space, time and the social realm are intrinsically linked. While an array of studies have tried to untangle these factors and their influence on human behaviour, hardly any have taken their effects into account at the same time. To disentangle these factors, we try to predict future encounters between students and assess how important social, spatial and temporal features are for prediction. We phrase our problem of predicting future encounters a…
Graph input representations for machine learning applications in urban network analysis
Understanding and learning the characteristics of network paths has been of particular interest for decades and has led to several successful applications. Such analysis becomes challenging for urban networks as their size and complexity are significantly higher compared to other networks. The state-of-the-art machine learning techniques allow us to detect hidden patterns and, thus, infer the features associated with them. However, very little is…
Avoiding pitfalls when using machine learning in HCI studies
Machine Learning (ML) has come of age and has revolutionized several fields in computing and beyond, including Human Computer Interaction.Historically, human subjects studies have adopted ML techniques for more than a decade, for example for activity recognition and wearable computing.However, there now exists a plethora of application domains where ML approaches are enriching interactive computing research.Here, we wish to highlight some of the …
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Avoiding pitfalls when using machine learning in HCI studies
Machine Learning (ML) has come of age and has revolutionized several fields in computing and beyond, including Human Computer Interaction.Historically, human subjects studies have adopted ML techniques for more than a decade, for example for activity recognition and wearable computing.However, there now exists a plethora of application domains where ML approaches are enriching interactive computing research.Here, we wish to highlight some of the …
Graph input representations for machine learning applications in urban network analysis
Understanding and learning the characteristics of network paths has been of particular interest for decades and has led to several successful applications. Such analysis becomes challenging for urban networks as their size and complexity are significantly higher compared to other networks. The state-of-the-art machine learning techniques allow us to detect hidden patterns and, thus, infer the features associated with them. However, very little is…
The role of space, time and sociability in predicting social encounters
Space, time and the social realm are intrinsically linked. While an array of studies have tried to untangle these factors and their influence on human behaviour, hardly any have taken their effects into account at the same time. To disentangle these factors, we try to predict future encounters between students and assess how important social, spatial and temporal features are for prediction. We phrase our problem of predicting future encounters a…
“What are they not telling me?” Learning machine learning
Machine Learning (ML) is increasingly accessible to users with limited knowledge of its theoretical foundations. However, misapplying it can lead to negative consequences. This paper reports on a qualitative study designed to reveal challenges that novices encounter when learning about basic ML concepts and building their first models. Twenty participants were introduced to fundamental ML concepts for classification through an interactive tutoria…
On the creativity of large language models
Large language models (LLMs) are revolutionizing several areas of Artificial Intelligence. One of the most remarkable applications is creative writing, e.g., poetry or storytelling: the generated outputs are often of astonishing quality. However, a natural question arises: can LLMs be really considered creative? In this article, we first analyze the development of LLMs under the lens of creativity theories, investigating the key open questions an…
Tracking the Temporal Evolution of Online Social Relationships in Times of Crisis
Social scientists have conceptualised different dimensions of human relationships, including knowledge, identity, and social support. At times of crisis, such as during a pandemic, social relationships can be disrupted, affecting the nature of interactions individuals have with others within their community and beyond. Understanding how relationships change, in both structure and content, can reveal how communities adapt and which connections are…
Computer Science (5 works) · Artificial Intelligence (3 works) · Psychology (3 works) · Human Mobility and Location-Based Analysis (2 works) · World Wide Web (2 works) · Adversarial Robustness in Machine Learning (1 work) · Art (1 work) · Artificial Intelligence in Games (1 work) · Cartography (1 work) · Citation (1 work)