Niyati is a statistician and machine learning researcher with a PhD in Data Science, where her thesis focused on Bayesian optimization for combinatorial structures. Her research lies at the intersection of statistical modeling, Bayesian inference, and optimization, with a focus on developing principled and scalable methods for complex and high-dimensional problems. She is particularly interested in leveraging advanced machine learning techniques to support scientific, medical, and climate-related research, aiming to use data-driven methods for meaningful and positive real-world impact.

Beyond research, Niyati enjoys yoga, gaming, hiking, traveling, and playing table tennis. She is also passionate about fitness and analog photography, which she values for its creative and reflective process.

Completed training placement with Microsoft.