Tutorial, 25th International Conference on Medical Image Computing and Computer Assisted Intervention, Singapore
The aim of this tutorial is to facilitate education on how to perform Federated Learning on both simulated and real world studies from software-based privacy-preserving techniques (e.g. DP), to hardware-based trusted execution environments (TEEs).
Talk, DST National Workshop on Machine Learning, Nirma University, India
This talk focuses on the importance and methods of making machine learning models, particularly deep learning models, interpretable and understandable. Computation and search has eliminated the need for domain-specific feature engineering. However, this has a caveat - deep models often behave like black boxes, and are prone to issues of trust, transparency, and safety, especially in mission-critical applications.