Read the report: Machine Learning Zone Report – November 2019 [PDF]The Machine Learning Zone was supported by the University of Oxford. In this activity, students connected with University of Oxford researchers working on things like how to make sure robots don’t crash into each other when they can’t talk to each other, why human brains are so good at learning, the ethical issues of robots working in hospitals and health care, and making computers that can learn to spot patterns in genetic data.
This zone saw an increase in students logged in and questions asked than the previous I’m a Researcher activity, Curiosity Carnival, in 2017. Students had lots of questions about careers and education in particular, including questions about studying and working at the University of Oxford.
Students from schools across England connected with nine researchers at the University of Oxford:
- Yee Whye Teh, who won this zone, is looking at the scientific principles underlying machine learning, to help us understand why and how things work in AI.
- Valerie Bradley is using data to develop and enhance methods of prediction.
- Nick Hawes works on AI methods to allow robots to plan and execute different behaviours.
- Mackenzie Graham is a researcher looking at relationships between technology and people.
- Lin Shuyu is a PhD student investigating the underlying principles of AI technology.
- Jun Zhao is researching the responsible use of AI with families.
- Jacob Laygonie is a researcher using maths to describe the differences between shapes in rules that computers can understand.
- Brian Zhang is using machine learning algorithms to help find patterns in genetic data.
- Anna Gautier studies and designs multi-robot systems, to help robots interact with each other.