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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 Nitay Alon whose research is at the intersection of cognitive science and AI. We talked about the fascinating topic of Theory of Mind, how this plays out in deceptive environments, multi-agent […]
AI and Theory of Mind: an interview with Nitay Alon Read More »
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 Maxime Meyer to chat about his current research, future plans, and how he found the doctoral consortium experience. Could you start with an introduction to yourself, where you’re studying and the
Studying the properties of large language models: an interview with Maxime Meyer Read More »
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 Prakhar Ganesh to learn about his work on responsible AI, which is focussed on the concept of multiplicity. We found out more about some of the projects he’s been involved in,
Studying multiplicity: an interview with Prakhar Ganesh Read More »
In this interview series, we’re meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We caught up with Oliver Chang whose research interests span deep reinforcement learning, autonomous vehicles, and explainable AI. We found out more about some of the projects he’s worked on so far, what drew him
Reinforcement learning applied to autonomous vehicles: an interview with Oliver Chang Read More »
In this interview series, we’re meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. Tanmay Ambadkar is researching the reward structure in reinforcement learning, with the goal of providing generalizable solutions that can provide robust guarantees and are easily deployable. We caught up with Tanmay to find out more
Telling agents what to do Our most powerful artificial agents cannot be told exactly what to do, especially in complex planning environments. They almost exclusively rely on neural networks to perform their tasks, but neural networks cannot easily be told to obey certain rules or adhere to existing background knowledge. While such uncontrolled behaviour might
Relational neurosymbolic Markov models Read More »
A number of prestigious AAAI awards were presented during the official opening ceremony of the Fortieth AAAI Conference on Artificial Intelligence (AAAI 2026) in Singapore, on Thursday 22 January. The winners are as follows: 2026 AAAI Award for Artificial Intelligence for Humanity The AAAI Award for Artificial Intelligence for Humanity recognises the positive impacts of
Congratulations to the #AAAI2026 award winners Read More »
The 40th AAAI Conference on Artificial Intelligence took place in Singapore from 20-27 January, the first time that the event has been held outside of North America. In our first social media round up we had a peak at the first half of the conference which hosted the tutorials, the bridge programme, and the doctoral
#AAAI2026 social media round up: part 2 Read More »
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. For the past couple of years, we’ve been meeting
The 40th AAAI Conference on Artificial Intelligence is currently taking place in Singapore, the first time that the event has been held outside of North America. The opening two days of the conference hosted the tutorials, the bridge programme, and the doctoral and undergraduate consortium, with the main conference – including the invited talks and
#AAAI2026 social media round up: part 1 Read More »
