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I-X Seminar Series: Cecilia Mascolo

Key Details:

Time: 13.00 – 14.30
Date: Wednesday 19 April
Location: I-X 5 Meeting Room, Level 5
Translation and Innovation Hub (I-HUB)
Imperial White City Campus
84 Wood Lane
London W12 7SL

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Speaker

Cecilia Mascolo

Cecilia Mascolo is the mother of a teenage daughter but also a Full Professor of Mobile Systems in the Department of Computer Science and Technology, University of Cambridge, UK. She is director of the Centre for Mobile, Wearable System and Augmented Intelligence. She is also a Fellow of Jesus College Cambridge and the recipient of an ERC Advanced Research Grant. Prior joining Cambridge in 2008, she was a faculty member in the Department of Computer Science at University College London. She holds a PhD from the University of Bologna. Her research interests are in mobile systems and machine learning for mobile health. She has published in a number of top tier conferences and journals in the area and her investigator experience spans projects funded by Research Councils and industry. She has served as steering, organizing and programme committee member of mobile and sensor systems, data science and machine learning conferences. More details at www.cl.cam.ac.uk/users/cm54

Talk Title

Wear-to-compute? Challenges of wearable computing and sensing for health.

Talk Summary

Wearable devices are becoming pervasive in our lives, from smart watches measuring our heart rate to wearables for the ear accompanying us in every virtual meeting. These devices are becoming, in theory, very good proxies for human behaviour. Yet, making the inference from the raw sensor data to individuals’ behaviour remains difficult. In this talk, Cecilia Mascolo will discuss where commercial systems have got to today and highlight the open challenges that these technologies still face before they can be trusted health measurement proxies. Namely, the ability to work in the wild, the sensitivity of the data versus centralisation of computation, the uncertainty of the prediction over the data. Cecilia Mascolo will use examples from her group’s ongoing research around on-device machine learning, “earable” sensing and uncertainty estimation for health application in collaboration with epidemiologists and clinicians.

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