Ohi Dibua is a Research Engineer whose work is data-centric. He focuses on synthetic data generation, bias in machine learning, and interpretability in deep models.

Ohi spent most of his formative years in Baltimore and Pittsburgh, before moving to the Bay Area for graduate school. He recently received his PhD in mechanical engineering from Stanford. His work there focused on combining uncertainty quantification, differential equations, and experimental design to understand physical systems. During his PhD,  Ohi developed an interest in Machine Learning. He explored this interest by becoming a software engineer at Nines, a Medical Imaging and Machine Learning start-up. There, he led the development of an FDA approved deep learning tool and worked on data management.