Andro Sabashvili

Andro Sabashvili transitioned to a data science career after obtaining a PhD in theoretical physics. Andro's data science journey commenced at Bank of Georgia, where he sharpened his skills in developing end-to-end machine learning projects, such as credit risk, propensity, and churn models using advanced machine learning algorithms. After designing a novel algorithm to automate the hyperparameter optimization process, which is currently patent-pending, he joined the startup company Dressler Consulting, where he led a team of data scientists building an automated machine learning platform. In his current role as a Staff Data Scientist at Majid Al Futtaim, Andro is focused on scaling up sales forecasting for thousands of stores, marketing mix modeling, marketing campaign impact estimation, and customer segmentation.


Session

09-26
14:25
30min
Adaptive Prediction Intervals
Andro Sabashvili

Adaptive prediction intervals, which represent prediction uncertainty, are crucial for practitioners involved in decision-making. Having an adaptivity feature is challenging yet essential, as an uncertainty measure must reflect the model's confidence for each observation. Attendees will learn about state-of-the-art algorithms for constructing adaptive prediction intervals, which is an active area of research.

Gaston Berger