Author Archives: Matteo Cagiada

Potholes: an ancient problem demanding modern solutions

You’re cycling along minding your own business when your front wheel suddenly drops into a deep, jagged pothole. The handlebars twist sideways, your heart lurches and, for a split second, you fight to stay upright. For cyclists and drivers, potholes aren’t just an annoyance: they can cause falls, break wheels, and lead to more serious injuries. However, potholes are a universal frustration for all road users and an everyday hazard that has plagued travellers throughout human history, not just in the age of the bicycles or cars.

David Wright / Potholes at the Level Crossing, Barrow Haven .
Accident involving a rider on a Voi hired e-scooter along Oxford Road in Old Marston. Source BBC.

Far from being a modern infrastructure failure, potholes predate the use of asphalt. Historical records show that they have been a persistent challenge for road builders across centuries and civilisations. Yet, despite advances in materials science and engineering, potholes still represent a significant drain on public finances and pose a hazard to drivers, cyclists and pedestrians alike. They are a persistent reminder that even our best roads are in a constant battle with the elements.

So what exactly are potholes, why do they form, and what are engineers doing to finally get ahead of them? Let’s dig in.

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Reflections on GRC CADD 2025: A Week of Insight, Innovation, and Baseball

Henry

Back in July, some very lucky OPIGlets ventured across the pond to discover life in Southern Maine (and Boston!). For someone visiting Boston for the first time, no trip would be complete without a Red Sox game—a thoroughly enjoyable highlight (see Figure 1). While we were there, we also went to Gordon Research Conference (GRC) on Computer Aided Drug Design (CADD).

A flock of OPIGlets taking in the Fenway Park experience at a Red Sox game.
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Conference feedback: Protein Society Annual Symposium

Recently, a couple of OPIG members had the opportunity to attend and present at the 39th Annual Symposium of the Protein Society—a not-for-profit scholarly society founded in 1985 that focuses on protein structure, function, and design—held in San Francisco.

The PS39 schedule was well designed, offering a balance between plenary talks, themed parallel sessions, and networking opportunities. A wide range of topics was covered, including transient protein states, supramolecular assemblies, proteostasis, and circadian clocks. This allowed us to follow areas of personal interest, both related and unrelated to our research, while exploring unfamiliar fields. Although many talks were biology-heavy, they were generally pitched at an accessible level for those from other disciplines (ie. the small molecules side of OPIG). Presentations almost always included results from both in silico and experimental approaches, with relatively few focusing exclusively on one or the other; a very nifty thing to see as people who mostly just dream of experimental validation! In contrast to our generalisable-model-focus, many of the researchers presenting had dedicated years to studying a single protein or system, uncovering its nuances in a way that made for some neat storytelling.

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NVIDIA Reimagines CUDA for Python Developers

According to GitHub’s Open Source Survey, Python has officially become the world’s most popular programming language in 2024 – ultimately surpassing JavaScript. Due to its exceptional popularity, NVIDIA announced Python support for its CUDA toolkit at last year’s GTC conference, marking a major leap in the accessibility of GPU computing. With the latest update (https://nvidia.github.io/cuda-python/latest/) and for the first time, developers can write Python code that runs directly on NVIDIA GPUs without the need for intermediate C or C++ code.

Historically tied to C and C++, CUDA has found its way into Python code through third-party wrappers and libraries. Now, the arrival of native support means a smoother, more intuitive experience.

This paradigm shift opens the door for millions of Python programmers – including our scientific community – to build powerful AI and scientific tools without having to switch languages or learn legacy syntax.

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Our future health: A new UK health research programme

Last week I walked into Boots  and, after giving some physical measurements, including my blood pressure and cholesterol levels, I gave a blood sample to be part of the Our Future Health initiative. Our Future Health (https://ourfuturehealth.org.uk/)  is set to become the UK’s largest health research programme ever. With the aim of recruiting five million volunteers across the country, it aims to revolutionise the way we detect, prevent and treat disease.

The breadth, depth and detail of Our Future Health makes it a world-leading resource. The data collected could hold the key to a wide range of health discoveries, such as:

  • Identifying early signals to detect disease much earlier.
  • Accurately predicting who is at higher risk of disease.
  • Developing better interventions and more effective treatments and technologies.

How’s it going so far?

Since the start of recruitment in July 2022 (delyed because of Covid), the programme has recruited over one million participants where:

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Conference summary: Generative AI in Life Science

This year I attended the second edition of Generative AI in Life Science (GenLife – https://genlife.dk/) and it was an enriching experience that I thoroughly enjoyed. Held in Copenhagen, the event brought together researchers from different areas of AI applied to the life sciences and provided a fantastic platform for networking, learning and sharing ideas. The programme included a mix of long and short talks from experts in the field, but also had a significant presence of emerging PIs, making the conference a perfect place to discover emerging groups in the field. Here I have collected some highlights of the talks I have enjoyed the most at the conference.

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