Sound is the best information carrier in the ocean. I work at the intersection of physics, engineering, and biology to develop computational methodologies and interpretation frameworks for extracting mid- to high-trophic level biological information from ocean acoustic data across multiple spatial and temporal scales.

My current research focuses on integrating physics-based models and data-driven methods to address two fundamental aspects of acoustic sensing:

• Sampling – how do we collect better data?
• Inference – what can we learn from the data?

A parallel but closely related focus of my research involves using echolocating bats and toothed whales as biological models for adaptive and distributed ocean sensing.

I enjoy working with people from diverse backgrounds, and am an active contributor to open-source scientific software (see echopype). I am passionate about data science education and have been the lead and co-lead of OceanHackWeek, a workshop dedicated to data science in oceanography, since 2018.

I lead the Echospace group and our research projects are funded by the National Science Foundation, the Office of Naval Research, and the National Oceanic and Atmospheric Administration.