In cities, air pollution can vary sharply from one street to the next. Fumes may linger between tall buildings, collect at busy junctions or drift towards a school gate. However, cities often lack the detailed forecasts needed to act before levels become dangerous. For Professor Soledad Le Clainche, an applied mathematician at the Technical University of Madrid and leader of the ModelFLOWs research group, better understanding how air moves through cities could help tackle one of Europe's biggest environmental health challenges. As part of an EU-funded research project called MODELAIR, Le Clainche is working with researchers in Belgium, the Netherlands, Sweden and the UK to make the invisible, highly local patterns of urban pollution easier for cities to understand.

This week saw researchers gather in Malmö at the ninth AAAI / ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) . We cast an eye over social media platforms to find out what participants got up to at the event. The 9th annual AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-26) is underway in Malmö. We are looking forward to a robust program full of educational and networking opportunities. Today at #AIES2026 in Malmö I joined the panel on Participation, Sovereignty, and Power in AI Governance with The Mitigation Paradox, joint work with Mina Schütz, Martin Kappes and Marc-Oliver Pahl. 3 takeaways: https://doi.org/10.5281/zenodo.23302284

Consider several research groups at a university that buy machines and put them into a shared cluster. Computing demands vary over time, and one group's quiet week may be another group's deadline crunch. Pooling allows the same hardware to be used much more efficiently than separate private clusters. But pooling raises a question: If you let your neighbour run on your machines this month, what claim do you have on theirs next month? In our IJCAI-ECAI 2026 paper,, we show that standard notions of fairness do not address this question and propose one that does.

The ninth AAAI / ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) is taking place in Malmö, Sweden from 12-14 October 2026. The panel discussion will take place on Tuesday 13 October. Find out more at the conference webpage . Lucy Smith is Senior Managing Editor for AIhub. Lucy Smith is Senior Managing Editor for AIhub.

Generative AI has changed mathematics forever. In August, artificial intelligence company OpenAI announced ten advances in mathematics and computer science made with their as-yet unreleased model Astra. The discoveries cover a wide range of mathematical fields, including geometry, cryptography and coding theory. These ten are just the latest in a rapidly growing list of mathematical breakthroughs made by generative artificial intelligence (AI) systems. OpenAI accompanied the announcement with a statement on "responsibility to the mathematical community".

Each year, a small group of PhD students are chosen to participate in the AAAI/SIGAI Doctoral Consortium . This initiative provides an opportunity for the students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. During 2026, we met with some of the students to find out more about their research and the doctoral consortium experience. Xiang Fang has been conducting his PhD research at Nanyang Technological University (NTU) in Singapore. Broadly speaking, his work focuses on multi-modal learning and embodied intelligence.

In a series of interviews, we're meeting some of the PhD students that were selected to take part in the Doctoral Consortium at the International Joint Conference on Artificial Intelligence and the 29th European Conference on Artificial Intelligence (IJACI-ECAI 2026) . This time, we hear from Mayra Elwes about her work developing machine learning methods for clinical time-series data. Tell us a bit about your PhD - where are you studying, and what is the topic of your research? I am a second-year computer science PhD student at the Institute for Biomedical Informatics at the University Hospital Cologne. My research focuses on the generalisation and domain adaptation of machine learning for clinical time-series forecasting, especially for clinic-to-clinic generalization scenarios.

Can you teach yourself to detect AI writing? AI is quietly reshaping writing. It's not just that prose is changing -- the very structure of written language is genuinely changing too. Did this article's introduction seem AI generated? What made you feel that way?

At the International Conference on Machine Learning (ICML 2026),, and presented their work Vision Language Models Cannot Reason About Physical Transformation . In this interview, William Yijiang Li tells us more about the research, the method the team used, and the controlled experiments they carried out. What is the topic of the research in your paper and why is it an interesting area for study? Our research asks a fairly fundamental question: do vision-language models actually understand how the physical world changes over time? Modern vision-language models are increasingly being used in areas such as robotics, embodied agents, and video understanding.

This post contains a list of the AI-related seminars that are scheduled to take place in the next couple of months. All events detailed here are free and open for anyone to attend virtually. Eleni Petraki and Damith Herath (University of Canberra) Raspberry PI Sign up here to join. Gaétan Hains, Paola Inverardi, and Alexander Wolf The Digital Humanism (DIGHUM) Initiative The talk will be livestreamed on YouTube here . Tyler Summers (University of Texas at Dallas) EPFL The Zoom link is here .