Volunteering Experience for Women in Data Science Conference (WiDS)
Table of Contents
About
Women in Data Science Conference (WiDS) is a Stanford University initiative for educating data scientists and supporting more women participation in this field.
The Women in Data Science Conference was held in Pune for the first time, with Ms. Sucheta Dhere as the ambassador.
You can watch me talking about my experience here.
Volunteering
I was a volunteer for WiDS 2019 as an Organising Committee member, and WiDS 2020 as part of a group study on Data Visualisation tools.
Organising Committee
For WiDS 2019, I served as a Core Committee member and a Website Development Team member. In my experience, this was one of the most extensively planned and well-organised event that I have been a part of. From 8 pre-conference events to the main conference, we saw a participation of 750+ people.
My contribution to the conference was as follows -
- Registrations Desk support
- Speed Networking event management - games, stalls, help in app installations
- Slideshows for WiDS
- Website development and maintenance for all 9-preconference event and videos on website.
I thoroughly enjoyed volunteering for the events while simultaneously attending the speaker sessions.
The event report can be found here.
DV Group Study
Pre-WiDS Pune 2020, I was a part of a group study on Data Visualisation (DV) Tools. The objective of the group study was to explore the need for DV Tools, compile resources on history and development, usage and implementation while gaining an understanding on when to pick which tool.
In particular, I studied the following tools -
- Marimekko Chart
- Heatmaps
- Win-Loss Sparkline
- Isoline Heatmaps
- Open High-Low Close Chart
- Kagi Chart
- Candlestick Chart
In addition to the ones above, I was part of discussions on other DV Tools including - Box plots, Violin charts, Sunburst diagrams, Waterfall charts, Scatter plots, Bubble charts, Ternary Contour plots, Hexagonal Binning, Chernoff Faces, Molecule Diagrams, Clustered Force Layouts.
Interestingly, I was able to use and extend the knowledge I gained through this study during my Senior Year project on Differential Privacy. We proposed differentially private DV Tool release, specifically working on Frequency Polygons and Bivariate Histograms.