Agus Sudjianto

Machine Learning for High-Risk Applications in Banking

Renowned statistician George Box once famously stated, “All models are wrong, but some are useful.” In a world where machine learning increasingly automates important decisions about our lives, the consequences of model failures can be catastrophic. It’s critical to take deliberate steps to mitigate risk and avoid unintended harm.

Lauren Rose Wilkes participated in MIT REU

Congratulations to our Data Science student Lauren Rose Wilkes who got selected to the Research Experiences for Undergraduates program at MIT. In Summer 2022, she worked under the supervision of Dr. Aleksander Madry in the Computer Science and Artificial Intelligence Lab. There she investigated machine learning model robustness in image classification by identifying the effect of poisoning the images most influential to the model prediction.