My research is focused on the intersection of deep learning frameworks and high performance computing. Specifically, my research focuses on resolving distributed deep learning training bottlenecks such as checkpointing, model/optimizer compression, and deep/machine learning framework co-design. I actively contribute to the MVAPICH2 project and its subprojects such as MVAPICH2-GDR (High Performance MPI for GPU clusters), and HiDL (High Performance Deep Learning).