Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we learn about drug and material design using generative models and Bayesian optimization, find out about a system for real-time monitoring for healthcare data, and explore domain-specific distribution shifts in volunteer-collected biodiversity datasets.
Interview with Ananya Joshi: Real-time monitoring for healthcare data
Ananya Joshi recently completed her PhD, where she developed a system that experts have used for the past two years to identify respiratory outbreaks (like COVID-19) in large-scale healthcare streams across the United States. In this interview, she tells us more about this project, how healthcare applications inspire basic AI research, and her future plans.
Interview with Onur Boyar: Drug and material design using generative models and Bayesian optimization
Onur Boyar is a PhD student at Nagoya university, working on generative models and Bayesian methods for materials and drug design. We met Onur to find out more about his research projects, methodology, and collaborations with chemists.
Interview with Filippos Gouidis: Object state classification
In this interview we chat to Filippos Gouidis about his work on object state classification. Filippos has developed a neurosymbolic method which combines a deep-learning approach with knowledge graphs. This method is both zero-shot and object agnostic, meaning an object state can be classified for objects not seen in the training data.
Exploring domain-specific distribution shifts in large-scale, volunteer-collected biodiversity datasets
Citizen science platforms have increased in popularity, fueling the rapid development of biodiversity foundation models. However, such data are inherently biased. In their work DivShift: Exploring Domain-Specific Distribution Shifts in Large-Scale, Volunteer-Collected Biodiversity Datasets, which won the AAAI outstanding paper award (AI for social alignment track), Elena Sierra, Lauren Gillespie and Moises Exposito Alonso tackled the challenge of quantifying the impacts of these biases on deep learning model performance. In this blog post, Elena and Lauren tell us more.
Automation applied to technical drawings in industry: Interview with Vasil Shteriyanov
In their paper Automating the Expansion of Instrument Typicals in Piping and Instrumentation Diagrams (P&IDs), presented at IAAI 2025, Vasil Shteriyanov, Rimma Dzhusupova, Jan Bosch and Helena Holmström Olsson focused on automation of technical drawings in industry. P&IDs are used to represent the layout of piping systems, instruments, and other equipment in large-scale infrastructure projects. In this interview, Vasil told us more about their work.
Gillian Hadfield on normative infrastructure for AI alignment
Gillian Hadfield is an economist and legal scholar turned AI researcher, and was one of the invited speakers at the 33rd International Joint Conference on Artificial Intelligence (IJCAI). AIhub ambassador Kumar Kshitij Patel caught up with her at the conference to find out more about her interdisciplinary research, career trajectory, path into AI alignment, law, and general thoughts on AI systems. You can listen to, and read, the interview here.
ICRA 2025
The 2025 IEEE International Conference on Robotics & Automation (ICRA) took place from 19-23 May, in Atlanta, USA. The event saw researchers gather for plenary talks, keynote sessions, a community day, workshops, tutorials, and more. You can find out what the participants got up to in our social media round-up, and check out the best paper winners here.
AAMAS 2025
Taking place at the same time as ICRA was the 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), which was held in Detroit, USA. The keynote speakers were Rada Mihalcea, Jeffrey Rosenschein and Virginia Dignum. During the conference, the AAMAS best paper awards were announced. You can find out which articles were honoured here.
AI Index report
The 2025 edition of the AI Index report is now available to read. Released on a yearly basis, the aim of the document is to provide readers with accurate, rigorously validated, and globally sourced data to give insights into the progress of AI and its potential impact on society. This year’s report contains eight chapters, and you can access the full pdf document here.
US House passes ten-year moratorium on state AI laws
On 14 May, House Republicans added a provision to the Budget Reconciliation Bill that would place a moratorium on states enforcing “any law or regulation regulating artificial intelligence models, artificial intelligence systems, or automated decision systems” for the next ten years. On 22 May, the House passed the bill, which now goes to the Senate. More than 140 organisations signed a letter to Congress asking for them to reject this proposal. “This moratorium would mean that even if a company deliberately designs an algorithm that causes foreseeable harm — regardless of how intentional or egregious the misconduct or how devastating the consequences — the company making that bad tech would be unaccountable to lawmakers and the public.”
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