+Lab @ University of Bristol

Who measures a city, who computes it, and who cares about the answer? @levijohnwolf.bsky.social argues cash-strapped local governments increasingly outsource these questions leaning on external datasets and tools, including AI, which "launder this experience from elsewhere”.

"It's there. It can't be changed. It's not adaptable." Nancy Grimm argues cities are built on an outdated "control" premise - treating social, ecological, and technological systems as separate and knowable - rather than the entangled, complex systems they actually are.

“The critical issue is where do we define the boundary?” Every model of a city has to stop somewhere - where, is never a clean answer. Michael Batty traces this unresolved problem back to the systems approach to architecture and planning in the 1960s.

Platform firms are moving into Global South cities where huge shares of the workforce already sit outside the formal economy. In this lightning talk, Anand Sahasranaman calls this "digital dualism": digital platforms reorganizing formal sectors while large informal sectors persist.

Why do cities exist at all? Luis Bettencourt sees that as a fundamental unresolved question in urban science, and one from which all others may follow.

He contends that an answer can be obtained in two ways – bottom up individual cost-benefit calculus (why live in this city right now?) versus top down emergent, citywide properties (what is the city for?). And the two don't always agree…

How do you build global liveability models that still hold up when validated locally? Angela Abascal argues that satellite data measures urban form and infrastructure at scale but misses lived experience.

"We know more about rivers in the Arctic than we do about urban rivers" That's the unresolved problem posed by Josh Dean in this lightning talk. Cities are shaped and used by people daily, yet we understand their ecological systems far less than remote wilderness.

"We don’t know if this is a good idea. We don’t know if this is necessary. We don’t know what the costs are of trying to impose such a limit." Lewis Dijkstra notes that many major policies treat urban sprawl as inherently bad.

Too much information can be as paralyzing as too little. In this lightning talk Madison Lore examines "noisy information environments" – settings where excessive, conflicting information makes it hard to plan well.

We're good at predicting cities as they are — but what about cities as they're about to become? Markus Schläpfer highlights that urban predictions largely rely on observing cities in their existing state.

Urban scaling gives us elegant ‘laws’ – Zipf’s law, gravity, percolation – but do we understand the behaviour behind them? In this lightning talk Chris Webster argues urban science and urban studies "don't know enough about each other" to connect these patterns to real economic theory.

Cities are built one material decision at a time — and those decisions may lock in for centuries. Hadi Arbabi points to a global material debt in cities, with carbon and energy demands still rising just to maintain them.

"How can cities build the capacity to adapt to futures they cannot yet imagine?" Juan Carlos Duque argues urban science is good at studying known trends — but not the changes we can't yet describe.

He traces a pattern across remote sensing, machine learning, quantum computing, and even soft robotics: technologies born outside urban studies keep reshaping what cities are, how they work, and what questions we should be asking about them.

What happens to infrastructure in fast-developing African cities under climate stress?

For this lightning talk, Anni Beukes draws on fieldwork with Slum Dwellers International to ask: under what conditions do urban service systems in informal settlements support collective adaptation, versus intensifying precarious, household-level self-provisioning?

Most of the data cities need will be “alien" - so says @darribas.bsky.social, posing an unresolved problem in urban science.

Testing theories, managing systems, and planning interventions all require data – but going forward, far more of it will be in the form of images, text, and other unstructured sources rather than traditional tables.

@timonm.bsky.social argues that cities face multiple, sometimes existential, challenges – yet decisions are still made in silos, by hazard or by sector, even as climate extremes cascade across infrastructure systems.

Cities are no longer urbanizing the same way - and we don't fully understand the implications. Ella McCoshan asks the unresolved question: what growing divergence in urbanization pathways means for land, resources, infrastructure, demography, wellbeing, and the economy?

"Who is likely to live where?" In this lightning talk, Felix Agyemang proposes that – despite decades of progress in urban land-use modelling – predicting where development happens, and who ends up living there, remains a key unresolved problem in urban science.

Steam 🚂 Jet engines ✈️ Air conditioning ❄️ Teleconferencing 🖥️ Now AI. Emmanouil Tranos unpacks the feedback loop between new technologies and cities — tech is born in cities, then reshapes what cities are and do.

More data won't save urban planning. In this lightning talk, @geoffboeing.com argues that the field's toughest problems — congestion, air pollution, and beyond — aren't just technical puzzles waiting for one more coefficient.

“You will be more influential than Jane Jacobs. More than Patrick Geddes. Not because you're smarter — because more people are living urban lives today than ever before, and the ideas we act on now will shape more of them than any generation's have.”