The winners of three International Joint Conferences on Artificial Intelligence (IJCAI) awards have been announced . These three distinctions are: the, the and the . The Research Excellence award is given to a scientist who has carried out a program of research of consistently high quality throughout an entire career yielding several substantial results. The winner of the 2026 Award for Research Excellence is Nicholas R. Jennings, Vice-Chancellor and President of Loughborough University, UK. Professor Jennings is recognized for his seminal contributions to the field of multi-agent systems, including algorithms for multi-agent coordination and the principles of human-agent teamwork, and for his pioneering applications of autonomous agents and multi-agent systems.

The Future of AI Research report, published in March 2025, aims to clearly identify the trajectory of AI research in a structured way. The report was led by outgoing AAAI President Francesca Rossi and covers 17 different AI topics . Members of the report team, and other selected AI practitioners, are taking part in a series of video panel discussions covering selected chapters from the report. In the next discussion in the collection, the four panellists tackle AI and scientific integrity. Lucy Smith is Senior Managing Editor for AIhub.

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 find out about time-series anomaly detection, delve into music generation, honour award winners, and catch up on the action from the RoboCup humanoid soccer league. We caught up with Thi Kieu Khanh Ho to find out more about her work on time-series anomaly detection, what inspired her to study AI, and what she plans to work on next. This interview is part of our series featuring the AAAI Doctoral Consortium participants. In the latest in our series of IJCAI interviews, AIhub ambassador Liliane-Caroline Demers spoke to François Pachet to find out more about his work on music generation with AI.

Humans have been successfully trained to spot AI-generated faces in a study led by researchers at the Australian National University (ANU) Emotions and Faces Lab. AI-generated deepfake faces have become so realistic that it is difficult for people to tell them apart from photos of real humans, contributing to increases in AI-related fraud. "Training on visual artifacts, like looking for a sixth finger or odd earrings, has had limited success, partly because the AI is getting too good, and fraudsters may avoid using pictures with obvious flaws anyway," lead researcher Associate Professor Amy Dawel said. "Our training directs people's attention to global qualities that differ between AI and human faces. AI faces tend to be more symmetrical, proportional and attractive, but without training we often think these are markers of being human."

The talk presented in this podcast, "Where do Ethics Belong in Artificial Intelligence?", It was presented at Oregon State University by Houssam Abbas (assistant professor of electrical engineering) and Alicia Patterson (assistant professor of philosophy) as part of an AI seminar series. "Engineering Out Loud" is a podcast from the College of Engineering at Oregon State University. It is for anyone who wants to know more about how engineering is changing the world. Hear from researchers about how they are tackling humanity's biggest challenges, including enabling access to clean water, preparing and recovering from natural hazards, and improving human the health and safety.

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. Anna Hedström (ETHZ) EPFL The Zoom link is here . Jie Chao (Concord Consortium) Raspberry PI Sign up here to join. Stefan Klein and Anna Bon The Digital Humanism (DIGHUM) Initiative The talk will be livestreamed on YouTube here .

Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. In this episode we chat with Rebecca for the second time about: why intelligence isn't everything, whether LLM's are even safe, AI governance and guardrails, moral assurance, under-specification problems, lack of interdisciplinary work in robotics, that AI shouldn't be sold as a solution to everything, sidelining of AI ethics, what are the actual benefits of AI, whether AI progress will widen inequality, and more Rebecca Raper is a robotics lecturer and researcher at Cranfield University. She authored the book Raising Robots to be Good: a practical foray into the art and science of Machine Ethics . She designed and leads the UK's first Robotics apprenticeship. This podcast was created and is run by Ben Byford and collaborators.

Protein engineering is a field primed for artificial intelligence research. Each protein is made up of amino acids; to optimize a protein function, researchers modify proteins by switching out one of 20 different amino acids for another. For a protein that is just 50 amino acids in length, this leads to approximately 1.13 10 potential combinations to test. This number of potential combinations, impossible to test in the lab, makes protein engineering an ideal challenge for AI. Modeling which of these combinations will give the best results is a perfect problem for the technology's massive computing power.

This year, RoboCup will be held in Incheon, South Korea, from 2-6 July. The event will see teams take part in competitions, training sessions, and a symposium. It's an exciting time for RoboCup, as there have been some updates to the leagues and competition format . Most prominently, the soccer leagues will have a primary focus on humanoid robots. A workshop focused on sharing projects, experiences, and innovations in educational robotics.

Many drug and antibody discovery pathways focus on intricately folded cell membrane proteins. When molecules of a drug candidate bind to these proteins, like a key going into a lock, they trigger chemical cascades that alter cellular behavior. Understanding how proteins fold and move is therefore essential for developing drugs that interact well with their targets. Artificial intelligence (AI) is a very useful tool to generate novel protein structures, but most systems - including Google DeepMind's AlphaFold - focus on producing static'snapshots' of proteins. Subtle rearrangements of atoms in structures called side chains, which influence a protein's interactions with other molecules, are not captured.