Introducing… Christina Last
What is your name?
Christina Last
What is your background?
I am a Research Data Scientist in the Research Engineering Group at the Turing, where I specialise in building machine learning solutions to understand our cities. My work bridges social data science, geographic machine learning, and machine learning operations. I enjoy working with city governments and international organizations on software and data science, in both developed and rapidly developing urban environments in the US and Vietnam. I have led various international research projects, most recently as a Senior Data Scientist collaborating with UNICEF to model air quality during COVID-19 lockdowns using machine learning.
Before joining the Turing, I was the Lead Data Scientist at a property technology start up, where I managed the development of the data ecosystem and machine learning algorithms to aid the real estate investment deal flow – from sourcing and purchasing to managing residential real estate. I hold a Bachelors from the Department of Geography at the University of Bristol, and completed a sabbatical at the University of California. I devote my spare time to building tech communities as the AICamp London Chapter Lead, most recently forming a partnership with Google London.
In one sentence, what is your role on the project?
I will combine my interests in data science and machine learning operations in Living With Machines, where I will develop cloud infrastructure to support collaborative work on the team’s research outputs.
What excites you about the project?
I enjoy working with scholars to discover thematically related research in a multidisciplinary setting, such as that of a university library. I believe my experience using natural language processing techniques to conceptualise document similarity, such as geographic and topical, will be important when developing toponym matching techniques to identify and link key geographic features to textual descriptions from archival documents.
What challenges do you see ahead?
Collaboration across radically different disciplines always poses challenges, be it aligning different workflows, collaborating through shared software platforms, or understanding each others perspectives on approaches to analysis. I am a firm believer that a common approach to infrastructure can simplify some of these challenges. As a new starter, I see my role in the project as understanding each researcher’s workflow, and using these to create common infrastructure for collaboration using the derived data generated so far in the project. We are investigating technologies such as Jupyter Hub.
What’s the last (non-work) book you read, exhibition or performance you saw?
I feel like a bit of a dork putting this down, but my last read was the Treatise of Human Nature by David Hume. Hume is an empiricist, and he rigorously argues in such delightfully readable tone that human knowledge is based on our experiences rather than reason. As an individual who finds great joy implementing logic using programming languages, it is often easy to forget that experience and emotion drives a lot of software design decisions.
Finally, where can people find out more about you and your work?
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