Interview with Nabanita Dash

Github: @dnabanita7  |  Twitter: @explorer_07

Where are you based?

"I am from India."

What do you do?

"I am a software developer at Julia Computing working on JuliaHub."

What are your specialties?

"I am proficient in both Python, Javascript development."

How and when did you originally come across OpenMined?

"During my sophomore year, I was going through a Google article on federated learning and that piqued my interest for privacy preserving AI. I was googling for more articles to understand federated learning better and I found Andrew Trask’s Udacity course Secure and Private AI. I got to know about OpenMined from there and joined the community. Although I finished the course, I was not ready to commit to the codebase. After a year or so, I tried again and I was able to contribute."

What was the first thing you started working on within OpenMined?

"I was interested in PySyft. I got the task of adding the slice object to PySyft. Maintainers helped me throughout to understand the code better and continue working on that. You can find detailed work here."

And what are you working on now?

"I am a member of the differential-privacy team at OpenMined. But as of now, I am writing documentation for HaGrid that will be shared with UN."

What would you say to someone who wants to start contributing?

"OpenMined community is very welcoming and everyone takes care of each other. You can always ask for help. There is a lot going on so you can jump right into where you want and start contributing. For me, going through tutorials and then starting to work on an issue works best. A lot of tutorials and example notebooks are created for beginners."

Please recommend one interesting book, podcast or resource to the OpenMined community.

"This is a really an exhaustive resource. Designing Data-Intensive applications is a fun read."