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Beyond Academia with Google’s Head of Universities, EMEA Partnerships

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About this event

What to expect

Explore how AI and data science move from academic research into real-world organisations with Google partnerships leader Christina Matteotti in Cambridge.

Taking place on Thursday 22 October 2026, from 4:00–5:00pm, this in-person Beyond Academia seminar offers University of Cambridge researchers and students a practical window into the opportunities and challenges surrounding applied AI. The session will be held in Room D at the West Hub, JJ Thomson Avenue, Cambridge.

From research to real-world deployment

Part of the University of Cambridge’s Beyond Academia: AI & Data Science Applications seminar series, the talk is designed to bridge the gap between high-level research and implementation inside organisations. It will examine the transformative role of data and artificial intelligence beyond the university environment, while helping attendees better understand non-academic career pathways.

The seminar series explores areas including:

  • The transition from academic AI and data science research to operational use
  • Technical and architectural challenges involved in implementing AI innovation
  • Organisational and operational considerations around real-world deployment
  • Opportunities for researchers applying their expertise outside academia
  • Career perspectives from leaders and professionals working beyond universities

Speaker and format

The invited speaker is Christina Matteotti, Head of Universities, EMEA Partnerships. The event is structured as an engaging, one-hour in-person talk rather than a hands-on workshop. Attendees will have plenty of opportunity to ask questions, making it a useful setting for exploring both practical implementation issues and possible career directions.

The seminar is organised by C2D3, the Cambridge Centre for Data-Driven Discovery. Everyone at the University of Cambridge is welcome, but the content is particularly aimed at PhD students, postgraduate researchers and Early Career Researchers. It may also be valuable for students interested in AI, data science, innovation partnerships or translating specialist research into impact within organisations.…

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