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Juliette Love

Juliette Love

Research Engineer at Google DeepMind focused on AI agents and APIs

London, United Kingdom

Summary

Juliette is a Research Engineer at Google DeepMind in London, where her work primarily focuses on agents and APIs. She has been instrumental in projects like Multimodal Live and Astra, and contributed to the Gemma open-source LLM. Her DeepMind work also includes post-training infrastructure and developing tools like Dramatron, a scriptwriting tool leveraging large language models. jujukin+3
Her expertise spans data visualization and visual journalism, cultivated through her academic work at Stanford and a significant internship with The New York Times Graphics team. At the Times, she created impactful visual stories on migrant detention, vote-by-mail policies, and COVID-19, and authored pieces on baseball's popularity and the cost of the Afghanistan war. This background underpins her ability to present complex information clearly. jujukin+1
Juliette holds both Bachelor's and Master's degrees in Computer Science with a specialization in Artificial Intelligence from Stanford University, where she also received a Terman Engineering Scholastic Award for academic excellence. Her academic work included research on designing school choice algorithms for the San Francisco Unified School District and explorations into educational inequities. jujukin+2
Beyond her professional and academic pursuits, Juliette has a strong interest in creative and analytical personal projects. These include developing algorithms for space-filling hexagons, deconstructing NFL draft data, analyzing MLB team spending, and exploring historical topics like Nazism in California and the shift in artistic color palettes. jujukin

Work

Education

Projects

Writing

A Robot Walks into a Bar: Can Language Models Serve as Creativity Tools for Comedians?

June 1, 2024

A paper (for FAccT 2024) co-authored with Piotr Mirowski, Kory Mathewson, and Shakir Mohamed, based on interviews with comedians about their use of LLMs.

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Gemma: Open models based on Gemini research and technology

February 1, 2024

Part of the Gemma team, which released a family of lightweight, state-of-the-art open models for developers and researchers.

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Designing School Choice for Diversity in the San Francisco Unified School District

January 1, 2021

A paper co-authored with a Stanford team on redesigning the seat assignment algorithm for the San Francisco Unified School District.

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Where Americans Could Vote by Mail in the 2020 Elections

August 1, 2020

An interactive article for The New York Times investigating each state's vote-by-mail rules during the 2020 elections.

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The Cost of Afghanistan, by the Numbers

March 1, 2020

An article for The New York Times assessing the human and monetary cost of the war in Afghanistan.

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Quantifying Artistic Style Changes Over Time

January 1, 2020

A paper analyzing the transition from Rococo to Neoclassical color palettes during the 18th century by fitting Gaussian curves to chromatic coordinates.

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Covering Covid-19 at the New York Times

January 1, 2020

A series of articles and contributions to reporting on COVID-19's impact, including cases in Latino communities, K-12 schools, and memorializing the first 100,000 American deaths.

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How Popular is Baseball, Really?

October 1, 2019

A front-page piece for The New York Times researching and explaining the popularity of baseball and misconceptions about its decline.

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Hobbies

Enjoys playing squash, having competed for Stanford University and previously at The Nueva School. gostanford+1

Interested in reading and cooking, with lists of her favorite books and recipes available on her personal website. jujukin+1

A fan of baseball's Milwaukee Brewers and football's Green Bay Packers, she has conducted data analysis related to these sports. jujukin+2