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SkillsCast

Using ML to Understand the Link Between Scenic Beauty and Wellbeing

datasets urban-analytics deep-learning wellbeing machine-learning data matters

18th February 2019 in London

This SkillsCast was filmed at Data Matters with Chanuki Seresinhe

SkillsCast About the Speaker

While architects, urban planners and policymakers have puzzled over this question for centuries, quantitative analyses have been held back by a lack of data on the beauty of our environment. Now, the vast volumes of geotagged images readily shared on the Internet, alongside developments in computer vision and deep learning, are opening up new opportunities to quantify aspects of the visual environment that were previously hard to measure.

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About the Speaker

Using ML to Understand the Link Between Scenic Beauty and Wellbeing

Chanuki Illushka Seresinhe

Chanuki Illushka Seresinhe is a data science researcher at the Alan Turing Institute. She also works as a senior data scientist at Channel 4. Chanuki's research entails using big online datasets and deep learning to understand how the aesthetics of the environment influences human wellbeing. Her research has been featured in the press worldwide including The Economist, Wired, The Times, BBC, Spiegel Online, The Guardian, The Telegraph and Scientific American. She received her PhD from the Data Science Lab, Warwick Business School, University of Warwick. Previously, she ran her own digital design consultancy advising clients on presenting their businesses successfully online.