Dr Linus Ericsson he/him

My research focus is to make sure that society benefits from the power of AI technologies whilst combating the ways it will be negative and disruptive.

My group develops machine learning methods to learn transferable representations of data, building efficient neural networks, and adapting these models across data shifts, all to help people solve problems reliably across different scenarios.

I am keen to form strong collaborations in climate/weather science, conservation/biodiversity, and biomedicine/medical imaging. Projects might involve multi-modal learning that fuses images, text, and other signals to monitor and support decision making in medical or climate contexts.

My supervising style is supportive and structured. We will set clear goals, meet regularly, review code and writing, and I will support you in planning your early career progression. I have previously co-supervised and mentored MSc and PhD researchers, who have progressed to industry research roles, e.g. at Meta.

I’m looking forward to building a respectful and inclusive group where everyone can contribute and grow. I very much see PhDs as colleagues and not subordinates. I value curiosity and kindness and am happiest when students come up with better ideas than mine.

An environment that embraces people from across society is both nicer to work in and provides differing perspectives that lead to better ideas. I have been involved as a mentor in the Women in Machine Learning (WiML) community, promoting the work of women and gender minorities in the field. I have also worked to improve access to conferences for those who cannot attend in person due to travel restrictions.

On a personal note, I love hiking around Scotland, playing board games and D&D with friends, and making music.