Posts’ Archive

Sometimes you have to admit that you have lost. Everyone sometimes loses a battle. In the last days, I’ve lost the battle against doom-scrolling. In this brief column, I try to process what happened.

I am now learning the difference between a “compendium” and other types of notebooks (in particular, commonplace books). Yet, I am here wondering: Is all of this structure really necessary?

This post resembles a rant more than an actual blog post; thus, I doubt that you will gain anything from reading this. However, I feel like I must share these thoughts in the hope of exorcising these sensations and, possibly, elicit a solution.

My mind and general interests are currently in a very hard spot. I am a Computer Science researcher. This brings me face-to-face with technology every day. And I do that with immense pleasure: I love keeping updated on the latest tech news and gadgets. I usually follow, every year, at least Apple’s WWDC, in an attempt to understand where the software I use every day is moving to. And I feel genuine excitement about any new announcement they make. As an example, working in the field of Human-Computer Interaction, I was genuinely thrilled when Apple introduced the “Dynamic Island” because, in a way, it was blurring the line between hardware and software.

In a world of endless tabs, blinking cursors, and distraction-driven design, writing on paper feels like a deliberate act of resistance. It’s slow. It’s tactile. It offers no shortcuts, no notifications, and no undo button. And yet, as a researcher, I find myself turning to pen and paper more and more often, especially when I need to think.

There is something strangely intimate about writing a blog post as a researcher. It is not a paper, a deliverable, or a grant proposal. It doesn’t carry the armor to criticism that peer review somewhat provides, and it feels strange to hit that “post” button without receiving the green light from other co-authors. It is, in a way, closer to a journal entry. And that’s where the lines begin to blur.

We are now living in an era where artificial intelligence (commonly known as AI) is no longer a distant concept confined to research laboratories or science fiction books. Instead, it has become a reality that intertwines with our daily lives (albeit, at times, not without issues¹). We interact with AI systems daily, often without even realizing it: from voice assistants that respond to our requests to recommendations from our favorite streaming platforms about which TV series to watch when we’re bored on the couch. And here lies the first warning sign: AI is no longer just an observer learning from our behaviors but is starting to influence them.

Research shows it isn’t… but it depends on users’ goals.

Balancing automation and human expertise when designing AI requires understanding your users’ needs.

Nowadays two problems affect science: the quantum necessary to publish scientific discovery is large. This not only heavily increases the time needed for publication, but it also impacts the time required to stay up to date with the…

The growing influence of AI brings benefits and risks. Our research explores how human-centred AI balances automation and human control in website usability evaluation. It shows how AI streamlines the detection of critical usability issues while augmented approaches also uncover less severe issues.

Recent advancements in Artificial Intelligence (AI), particularly through Deep Learning and large-scale datasets, have led to the creation of powerful models like OpenAI’s GPT-n. These models have significantly enhanced Natural Language…

Brain tumors are tricky to diagnose and treat due to the brain’s complexity. Detecting them quickly improves patient chances. Our study explores using Artificial Intelligence (AI), specifically deep learning, to save time and resources in finding tumors from imaging. We tested an AI model on MRI scans and achieved about 99% accuracy. We also emphasize the importance of explaining and being transparent about how the AI works to ensure human control and safety in the diagnostic process.

Dementia affects ~55 million individuals worldwide, with Alzheimer’s disease (AD) being the predominant type. Artificial Intelligence (AI) may aid in its diagnosis. We propose and evaluate multi-modal models for the task, incorporating eXplainable Artificial Intelligence for diagnostic transparency.

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