Prof. Hannah Fry

Mathematician & Science Presenter

Hannah Fry is a Professor in the Mathematics of Cities at the Centre for Advanced Spatial Analysis at UCL where she studies patterns in human behaviour. Her research applies to a wide range of social problems and questions, from shopping and transport to urban crime, riots and terrorism. She is also a best-selling author, a science presenter and the host of popular podcasts and television shows.

"There’s a mathematical angle to almost anything"

Topics

Data and Bias
What Data Can (and Can?t) Tell us About Ourselves
The Trouble with Automation
The Joy of Data
The Winner's Handbook

Languages

She presents in English.

How she presents

Hannah’s talks have resonated with audiences everywhere, earning her international recognition. In response to growing demand, Hannah has journeyed far and wide to share her intriguing stories and thought-provoking perspectives.

Publications

2021
Rutherford & Fry’s Complete Guide to Absolutely Everything (Abridged)
2019
Hello World
2016
The Indisputable Existence of Santa Claus
2015
The Mathematics of Love

Talk to us about Hannah Fry

In Detail

In 2023, Bloomberg launched “The Future with Hannah Fry,” a new series where Hannah explores transformative breakthroughs in science, technology and society. Renowned for her acclaimed BBC documentaries such as “The Secret Genius of Modern Life” and “Making Sense of Cancer,” and “Contagion” (a science experiment aimed to simulate what would happen if a deadly pandemic were to come to UK, two years before the predictions came true!), she also authored the book “Hello World,” which won the 2020 Asimov Prize. Through her YouTube videos, podcasts and radio series “The Curious Cases of Rutherford and Fry,” Hannah skilfully breathes life into mathematical concepts.

What she offers you

Hannah delivers fascinating talks, presenting unconventional examples ranging from tracking serial killers to analysing cow fertility and predicting malarial water sources, to explore the collection, utilisation, reliability and limitations of data and models.