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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 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 »
Jamillah Knowles & Digit / Pink Office / Licenced by CC-BY 4.0 Abstract 2025 marked a pivotal shift in AI – from testing to deployment. This happened as generative and agentic systems became essential in key sectors worldwide. This feature highlights the major AI ethics and policy developments of 2025, and concludes with a forward-looking
Top AI ethics and policy issues of 2025 and what to expect in 2026 Read More »
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 explore multi-agent systems and collective decision-making, dive into neurosymbolic Markov models, and find out how robots can acquire skills through interactions with the physical world.
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
Image Credit: Jiajun Wu, Yunzhi Zhang, Hong-Xing Yu, Joy Hsu, Jiayuan Mao. Discovering Hybrid World Representations with Co-Evolving Foundation Models. In Proceedings of the Annual AAAI Conference on Artificial Intelligence, Emerging Trends in AI (ETA) Track, 2026. In the latest issue of AI Matters, a publication of ACM SIGAI, Ella Scallan caught up with Jiajun
Learning to see the physical world: an interview with Jiajun Wu Read More »
In the latest issue of AI Matters, a publication of ACM SIGAI, Ella Scallan caught up with Aishwarya Agrawal to find out more about her research, what most excites her about the future of AI, and advice for early career researchers. You were awarded an Honourable Mention for the 2019 AAAI / ACM SIGAI Doctoral
Clarote & AI4Media / AI Mural / Licenced by CC-BY 4.0 Interactive AI: From tool to companion AI is no longer just a translator or image recognizer. Today, we engage with systems that remember our preferences, proactively manage our calendars, and even provide emotional support. This is interactive AI. Unlike traditional software, these systems are:
Governing the rise of interactive AI will require behavioral insights Read More »
Congratulations to Sven Koenig on winning the 2026 ACM/SIGAI Autonomous Agents Research Award. This prestigious award is made for excellence in research in the area of autonomous agents. It is intended to recognize researchers in autonomous agents whose current work is an important influence on the field. Professor Sven Koenig was recognised “for his work
Sven Koenig wins the 2026 ACM/SIGAI Autonomous Agents Research Award 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
