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 delved into the history of RoboCup, learned about time series, studied multiplicity, and found out more about Theory of Mind.
Manuela Veloso on the history of RoboCup
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.
What we’ve learned from 25 years of automated science, and what the future holds
We’re excited to launch a new series, where we’ll be 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.
Yan Liu on time series
Each year the AAAI recognizes a group of individuals who have made significant, sustained contributions to the field of artificial intelligence by appointing them as Fellows. Yan Liu, University of Southern California was elected as a 2026 Fellow “for significant contributions to machine learning and development of widely recognized models for time series and spatiotemporal data analysis”. We met with Yan to find out about her research, why time series are such a fascinating topic, and her career path to date.
AIhub coffee corner: AI, kids, and the future – “generation AI”
The AIhub coffee corner captures the musings of AI experts over a short conversation. This month, Sanmay Das, Tom Dietterich, Sabine Hauert, Michael Littman, and Ella Scallan tackled the topic of young people and what AI tools mean for their future.
Studying multiplicity
What is multiplicity, and what implications does it have for fairness, privacy and interpretability in real-world systems? These are some of the questions we explored with Prakhar Ganesh.
Investigating the properties of large language models
Maxime Meyer is a PhD student in Singapore focussed on developing theoretical models to predict the performance of LLMs. We caught up with him to find out more.
AI and Theory of Mind
Nitay Alon’s 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 systems, the interdisciplinary nature of this field, when to use Theory of Mind, and when not to, and more.
Resource-constrained image generation and visual understanding
In this interview, Aniket Roy tells us about his research exploring how modern generative models can be adapted to operate efficiently while maintaining strong performance.
A principled approach for data bias mitigation
In their paper, A Principled Approach for Data Bias Mitigation, presented at AIES 2025, Bruno Scarone, Alfredo Viola, Renée J. Miller and Ricardo Baeza-Yates introduced a new way to measure data bias, along with a mitigation algorithm that comes with mathematical guarantees. In this blog post, Bruno tells us more.
A multi-armed robot for assisting with agricultural tasks
How can a robot safely manipulate branches to reveal hidden flowers while remaining aware of interaction forces and minimizing damage? Madhav Rijal provides insights into the method which was presented at the International Conference on Intelligent Robots and Systems (IROS).
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