'This is an apartheid regime' Israeli soldiers and settlers have killed at least 11 Palestinians across Gaza and the occupied West Bank, according to Palestinian officials and local media, in the latest bloodshed to occur during a "ceasefire" announced in October. In Gaza, at least seven Palestinians were killed in a series of Israeli attacks, including a child who died from injuries sustained days earlier, while 21 were reported on Tuesday to have been injured over a 24-hour period. Another Palestinian man was later killed on Tuesday in an Israeli drone attack near the Sheikh Nasser neighbourhood, east of Khan Younis. In northern Gaza, a Palestinian woman was killed when Israeli naval forces shelled tents sheltering displaced families northwest of Beit Lahiya. Verified video obtained by Al Jazeera showed the body of Abdullah Dawas, a child wrapped in white cloth for burial, after he succumbed to injuries 10 days after being shot in the head near al-Fakhoura clinic in northern Gaza's Jabalia refugee camp.

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We hear from Xinwei Song about the two main research threads she's worked on so far, plans to expand her investigations, and what inspired her to study AI. Could you start with a quick introduction - where are you studying, and what is the topic of your research? My research primarily focuses on strategic interactions in networked multi-agent systems. Could you give us an overview of the research you've carried out so far during your PhD? My research to date consists of two main threads, which complement each other in exploring strategic interactions from different perspectives.

How do you go about integrating causal knowledge into decision systems or agents? We sat down with Matteo Ceriscioli to find out about his research in this space. This interview is the latest in our series featuring the AAAI/SIGAI Doctoral Consortium participants. Could you start by telling us a bit about your PhD - where are you studying, and what's the broad topic of your research? The idea is to integrate causal knowledge into agents or decision systems to make them more reliable.

What I've learned from 25 years of automated science, and what the future holds: an interview with Ross King We're excited to launch our new series, where we're speaking with leading researchers to explore the breakthroughs driving AI and the reality of the future promises - to give you an inside perspective on the headlines. Our first interviewee is Ross King, who created the first robot scientist back in 2009. He spoke to us about the nature of scientific discovery, the role AI has to play, and his recent work in DNA computing. Automated science is a really exciting area, and it feels like everyone's talking about it at the moment - e.g. But you've been working in this field for many years now. In 2009 you developed Adam, the first robot scientist to generate novel scientific knowledge. Could you tell me some more about that? So the history goes back to before Adam.

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. Minghong Geng recently completed his PhD and is now working as a postdoctoral researcher at Singapore Management University. We sat down to discuss his research on multi-agent systems. Firstly, congratulations on completing your PhD! What is the general topic of your research? I work on multi-agent systems.

RoboCup is an international competition that promotes and advances robotics and AI through the challenges presented by its various leagues. We got the chance to sit down with Professor Manuela Veloso, one of RoboCup's founders, to find out more about how it all started, how the community has grown over the years, and the vision for the future. I think it would be very interesting to go right back to the beginning and hear how RoboCup got started. What was the initial idea, and how did it get set up? So we are talking about the mid-90s. In terms of the research in those days, it was the beginning of the internet and many AI and computer science researchers were focused on the internet, first on sophisticated search algorithms, on natural language understanding, on information retrieval, and then on software agents and machine learning applied to digital information. From what I recall, there was a smaller group of researchers who were interested in actual, physical robots, and in particular in AI and robotics.

In their paper LLMasMMKG: LLM Assisted Synthetic Multi-Modal Knowledge Graph Creation For Smart City Cognitive Digital Twins, which was published in the AAAI Fall Symposium series, and introduced an approach that leverages large language models to automate the construction of synthetic multi-modal knowledge graphs specifically designed for a smart city cognitive digital twin. Here, Sukanya tells us more about cognitive digital twins, the framework they employed, and some key results. Could you start by introducing the idea of smart city cognitive digital twins and why this is an interesting area for study? Cities grow increasingly complex and interconnected, demanding sophisticated tools for management. A cognitive digital twin (CDT) serves as an AI-enabled virtual replica that models the dynamic interplay of physical and social systems, enabling simulations, predictions, and optimized operations.

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We sat down with Abdelrahman Sayed Sayed to chat about his work on formal verification applied to autonomous vehicles. Could you tell us a bit about where you're studying and the broad topic of your research? My PhD topic is formal verification of neural ODE (ordinary differential equations) for safety evaluation in autonomous vehicles. Could you say something about formal verification and why it's such an important topic?

Nancy Guthrie sheriff's appalling past revealed: Beat handcuffed suspect so badly he needed intensive care, used VILE language about woman and lied in sworn statement Vance grounded at White House as Iran peace talks in turmoil and Trump declares: 'I expect to be bombing' New'Hollywood dose' pill: A-listers hooked on'youth elixir' that dermatologists say is anti-ageing, shrinks pores, smooths wrinkles... and even banishes rosacea Days after we got engaged, the love of my life told me he'd killed a man and buried him in a bog. I reported him to police... but then I made this irreversible mistake Ark of the Covenant's final resting place pinpointed by archaeologists as fresh search begins Ritzy Bay Area town torn apart after teacher's daughter, 16, crashed car while speeding and killed four friends... then posted a TikTok video that poured fuel on the flames Jordon Hudson extends her control over Bill Belichick's empire with secret move that is set to leave his family and friends furious Two CIA officers killed in Mexico when their car skidded off ravine and exploded after meeting about bust of'largest ever drug lab' Life-threatening cantaloupe recall in four states upgraded to FDA's highest risk level... 'reasonable probability of death' AMANDA PLATELL: Why Sarah Ferguson - with the ghost of Princess Diana at her side - is ready to sensationally blow up the Royal Family. She knows ALL their secrets... Trump confronts Xi as US forces seize Chinese ship carrying mysterious'gift' to Iran Team USA Olympics star Noah Lyles slammed for'horrible' reaction to his wife's wedding dress reveal In honour of the Queen's (purple!) reign: Kate mirrors late monarch's colourful wardrobe and wears her pearl earrings and necklace How to lose weight when perimenopause sabotages your metabolism: I'm a trainer but when I hit 46, I piled on the pounds overnight. The new'posh' drug that's easier to order than Uber Eats - and why all my middle-class friends have ditched booze and cocaine for it: JANA HOCKING Fury as murderer marries pen pal behind bars... as teenage victim's mom says: 'I'm serving a life sentence without my son' Autistic woman, 24, worked hard to build independent life for herself... now she's PARALYZED thanks to selfishness of stranger Chilling warning from Nobel physicist as date is set for humanity's final destruction The winner of the Nobel Prize in Physics has issued a stark warning to humanity, saying it could face an existential catastrophe within roughly 35 years. David Gross, who shared the 2004 Nobel Prize in Physics, warned that'due to the danger of nuclear war,' humankind may have just a little more than three decades left.

Ritzy Bay Area town torn apart after teacher's daughter, 16, was behind wheel when four friends died in high-speed crash... then she posted a TikTok video that poured fuel on the flames Two CIA officers killed in Mexico when their car skidded off ravine and exploded after meeting about bust of'largest ever drug lab' Nancy Guthrie sheriff's appalling past revealed: Beat handcuffed suspect so badly he needed intensive care, used VILE language about woman and lied in sworn statement Trump confronts Xi as US forces seize Chinese ship carrying mysterious'gift' to Iran New'Hollywood dose' pill: A-listers hooked on'youth elixir' that dermatologists say is anti-ageing, shrinks pores, smooths wrinkles... and even banishes rosacea Days after we got engaged, the love of my life told me he'd killed a man and buried him in a bog. I reported him to police... but then I made this irreversible mistake Ark of the Covenant's final resting place pinpointed by archaeologists as fresh search begins Fury as murderer marries pen pal behind bars... as teenage victim's mom says: 'I'm serving a life sentence without my son' Insiders claim failed AI rollout could be to blame for Tim Cook's departure from Apple - as one says'the AI era requires a different kind of leadership' Life-threatening cantaloupe recall in four states upgraded to FDA's highest risk level... 'reasonable probability of death' AMANDA PLATELL: Why Sarah Ferguson - with the ghost of Princess Diana at her side - is ready to sensationally blow up the Royal Family. She knows ALL their secrets... Team USA Olympics star Noah Lyles slammed for'horrible' reaction to his wife's wedding dress reveal In honour of the Queen's (purple!) reign: Kate mirrors late monarch's colourful wardrobe and wears her pearl earrings and necklace US troops board second tanker as Iran is accused of breaking ceasefire'numerous times' How to lose weight when perimenopause sabotages your metabolism: I'm a trainer but when I hit 46, I piled on the pounds overnight. The new'posh' drug that's easier to order than Uber Eats - and why all my middle-class friends have ditched booze and cocaine for it: JANA HOCKING Autistic woman, 24, worked hard to build independent life for herself... now she's PARALYZED thanks to selfishness of stranger READ MORE: McDonald's is testing humanoid ROBOTS in Shanghai During last year's shambolic Beijing robot half marathon, humanoid machines tripped, shuffled, and occasionally shattered into pieces as they collapsed under the strain. But 12 months later, supporters looked on in awe as a new generation of speedy robotic racers left the human athletes in the dust.