If you have ever taken any training modules or learned something new by going through the official documentation, the material you used was probably written or co-authored by one or many contributors. These individuals often are volunteers who offer their time and expertise to cover knowledge gaps in our portfolio or to keep the existing content current.
In this series, we’ll be interviewing repeat contributors to the Microsoft Learn platform to get to know them better and to learn what motivates them to keep contributing.
Today we are interviewing Manasa Ramalinga. Manasa is a Principal Cloud Solution Architect and an experienced data science leader from the US Customer Success team. In this role, she enables and empowers Microsoft customers and partners to leverage Azure AI/ML services to build innovative, impactful, and scalable data science solutions. She was nominated for this spotlight interview by Azure architectures team for her work as an expert in Azure architectures in key industry scenarios, authoring architectures about risk prediction in surgeries, real-time anomaly detection for conveyor belts (in manufacturing), and how to predict student attrition.
Some of her recent Microsoft Learn contributions are:
- Risk prediction models for surgeries—Azure Architecture Center
- Real-time anomaly detection for conveyor belts—Azure Architecture Center
- Predicting student attrition—Azure Example Scenarios
Meet Manasa Ramalinga
Sherry: Hi, Manasa. It’s wonderful that you could join us today. I’d like to start by asking you to tell us a bit about yourself and your expertise and experience.
Manasa: I’ve been a data scientist and solution architect for more than a decade now, enabling customers and partners to build data centric organizations. I lead artificial intelligence/machine learning initiatives to build data science solutions and repeatable accelerators on the Azure platform. I also founded and led the Women in Data Science (WiDS) technical charter at Microsoft. This charter aims to improve female representation in the data science community. Finally, I’m a reviewer for and contributor to the Microsoft Journal of Applied Research (MSJAR), a Microsoft-internal journal. I help select some of the highest quality research from across Microsoft for publication in this journal.
Sherry: You are one of the top contributors to Azure Architecture Center (AAC). What inspired you to start contributing, and what motivates you to keep contributing?
Manasa: I’m passionate about empowering our customers and partners with Azure AI/ML technologies to become leading data-centric organizations. The solutions I co-develop are often niche, but my goal is to take niche solutions and impact an array of industries and customers. AAC offers a way for me to share repeatable, scalable architectural patterns and reach millions of customers who are embarking on their AI/ML journeys on Azure.
Sherry: What advice would you give to people who want to start contributing to open-source content?
Manasa: The impact one can have by sharing insights and knowledge on a platform like Azure Architecture Center is exponential. Many of our customers and partners make critical decisions about choosing Azure based on what they can learn and accomplish with our platform through AAC. As the Microsoft technical community builds niche solutions, I highly encourage them to share their knowledge and architectures via AAC to ensure broader platform adoption and impact. As Bill Gates says, “Power comes not from knowledge kept, but from the knowledge shared.”
Sherry: What a great quote about the impact of sharing our knowledge and skills, which is especially relevant to contributors like yourself! One purpose of this interview is to highlight the person behind the contributions, so tell us something about yourself aside from work. What do you do with your free time?
Manasa: In my free time, I like to hike, bike, and cook delicious meals for my family and friends. I have been a lifelong learner, and I’m currently trying my hand at playing piano and at skiing to give some tough competition to my children.
Sherry: It sounds like you keep yourself very busy, so we truly appreciate that you made time for us. Thanks, Manasa!
Manasa's top 3 contributions to Microsoft Learn
- Risk prediction models for surgeries - Azure Architecture Center | Microsoft Learn
- Real-time anomaly detection for conveyor belts - Azure Architecture Center | Microsoft Learn
- Predict student attrition - Azure Example Scenarios | Microsoft Learn
To keep up with Manasa, follow her on LinkedIn: https://www.linkedin.com/in/trmanasa/
To learn more about contributing to Microsoft Learn, visit the Microsoft Learn documentation contributor guide.
Thanks to Melia Hughes from the Voice of the Contributor program for putting these spotlight stories together.