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Context inference and control in AI-driven cyber physical systems

Venue: Birkbeck Clore Management Centre

Smart devices are becoming increasingly affordable and ubiquitous; whether they are seamlessly embedded in the environment, or carried by people and robots, they continually generate sensor data about the world that surrounds them. Recent advances in machine learning have revolutionised the ability of smart sensors to perceive and interpret context, infer human activities and react to human preferences. In this talk, I will highlight challenges and opportunities in designing machine learning techniques to solve the problems of indoor positioning and mapping. I will then show how the power of machine learning, can become a severe vulnerability, in the absence of sufficient measures to protect the privacy of individuals.

(This joint event is organised with Computing Women@BBK)


Niki Trigoni is Professor at the Oxford Department of Computer Science, heading the Cyber Physical Systems Group. Her interests lie in localisation protocols for GPS-denied environments using a variety of sensor modalities, including inertial, visual, magnetic and radio signals. She has applied her work to a number of application scenarios, including agile asset monitoring for construction sites, mobile autonomy with humans and robots, and track worker localisation for safety and efficiency. Trigoni is also Director of the CDT on Autonomous and Intelligent Machines and Systems (2014-2022) and Founder of the Navenio Oxford spinout.  

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