Season 1 | Episode 2

Machine Learning for High Risk Applications with Parul Pandey

On this episode, we’re joined by Parul Pandey, Principal Data Scientist at and co-author of Machine Learning for High-Risk Applications.

Although AI is being widely adopted, it poses several adversarial risks that can be harmful to organizations and users. Listen to this episode to learn how data scientists and ML practitioners can improve AI outcomes with proper model risk management techniques.

About the guest
Parul Pandey has a background in Electrical Engineering and currently works as a Principal Data Scientist at Prior to this, she was working as a Machine Learning Engineer at Weights & Biases. She is also a Kaggle Grandmaster in the notebooks category and was one of Linkedin’s Top Voices in the Software Development category in 2019. Parul has written multiple articles focused on Data Science and Software development for various publications and mentors, speaks, and delivers workshops on topics related to Responsible AI. She is currently part of the “The 2023 Kaggle AI Report” as an area chair and section editor, focusing on the section dedicated to the theme of continued studies of AI ethics.