opinions

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 […]

opinions

The Machine Ethics podcast: moral agents with Jen Semler

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. Moral agents with Jen Semler This month, Ben met in-person with Jen Semler. They chatted about what AI is, philosopher and […]

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 […]

AAAI, ACM SIGAI, AI Matters, opinions

Learning to see the physical world: an interview with Jiajun Wu

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 […]

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