ACM SIGAI

AAAI, AAAI Doctoral Consortium, AAAI2026, ACM SIGAI, opinions

Scaling up multi-agent systems: an interview with Minghong Geng

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 […]

AAAI, AAAI Doctoral Consortium, AAAI2026, ACM SIGAI, opinions

Studying the properties of large language models: an interview with Maxime Meyer

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 […]

AAAI, ACM SIGAI, AIES, articles, IJCAI, monthly digest, RoboCup

AIhub monthly digest: February 2026 – collective decision making, multi-modal learning, and governing the rise of interactive AI

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. […]

AAAI, AAAI Doctoral Consortium, AAAI2026, ACM SIGAI, opinions

Reinforcement learning applied to autonomous vehicles: an interview with Oliver Chang

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 […]

AAAI, AAAI Doctoral Consortium, AAAI2026, ACM SIGAI, opinions

Extending the reward structure in reinforcement learning: an interview with Tanmay Ambadkar

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 […]

Scroll to Top