Funda Gunes

 

Funda Gunes

My research interests include using well-established statistical techniques in data-driven decision making alongside machine learning modeling. Having spent ten years in industry building end-to-end predictive modeling pipelines with a strong statistics background made me realize that algorithm-based modeling can be significantly enhanced by using traditional statistical techniques. Some examples include using confidence regions for hyperparameter tuning, best linear unbiased predictors for efficient feature engineering, and generalized additive models for intelligible machine learning models. I am also passionate about mentoring and advising students and supporting women in the data science community by creating learning and networking opportunities through partnerships with leading companies and accomplished professionals.