Women in Data Science | IBM Code Bristol

IBM Code Bristol in collaboration with Jean Golding Institute at Bristol University is proud to host the first Women in Data Science event at Bristol to coincide with the annual Global Women in Data Science (WiDS) Conference held at Stanford University.

The Women in Data Science (WiDS) initiative aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field.

Our event has an all-female lineup of speakers and includes various Tech Talks and a panel discussion.

Agenda :

3 pm - 3.15 pm
Introduction

Tech Talks

3.15 pm - 3.45 pm - ‘Spot the odd’ - Anomaly Detection in time-series data

Speaker - Dr. Elena Hensinger
Senior Data Scientist

Predicting upcoming failures in machinery can save time, money and work. As these failures tend to be a rare event, this task is an example of anomaly detection.
Your client is keen to provide you with time series data from sensors that help monitor their machinery, and failure logs from previous repairs and maintenance. What an exciting project!
And then you get the data…
This talk will discuss real-life challenges with time-series data and discuss ways to provide value to your client, no matter the quality of data.

3.45 pm - 4.15 pm - Machine learning in speech applications - the smaller, the better

Speaker - Alexandra Craciun
Audio Algorithms Engineer at XMOS

In the world of machine learning, data and algorithms hold the power. The more data you have, the better you can cover the multitude of scenarios you expect in real life. At the same time, in order to achieve human-like classification precision, the algorithms become more and more complex. Yet many of these algorithms need to run on low-power devices such as mobile phones, where power consumption becomes as critical as performance. In this talk we will look into voice activity detection and discuss optimisation approaches for designing an efficient low-power algorithm to detect speech.

Short Break

4.25 pm - 5 pm - The Turing Way: A community built on a culture of collaboration

Speaker - Malvika Sharan
Community Manager | Research Associate at The Alan Turing Institute

In this session Malvika talks about lowering barriers for people (with a focus of women and other minority groups) to participate in online data science projects.
This talk will introduce The Turing Way project that aims to bridge the gap between innovative data research techniques and best practices that make them accessible and comprehensible for everyone.

5 pm - 5.30 pm - Trusting machines with robust, unbiased and reproducible AI

Speaker - Dr.Margriet Groenendijk
Global Developer Advocacy lead for Data Science at IBM

Learn about how bias can take root in machine learning algorithms and ways to overcome it. From the power of open source, to tools built to detect and remove bias in machine learning models, there is a vibrant ecosystem of contributors who are working to build a digital future that is inclusive and fair. Learn how to achieve AI fairness, robustness and explainability. You can become part of the solution.

5.30 pm - 6.00 pm - Panel discussion
Panelists
Elena Hensinger
Alexandra Craciun
Malvika Sharan
Margriet Groenendijk
Moderator - Yamini Rao

WHO SHOULD ATTEND?
The event is open to everyone, regardless of gender, who is interested in engaging with and learning from the local data science community.