In October 2023, I took on a 3-year project as lead of NMFS Open Science, which is helping adoption of Open Science and Open Data practices across NOAA Fisheries as part of a larger data modernization effort. I am also co-organizer of the Inter-agency R User Group (federal agencies) and NMFS Openscapes. Since 2020, I have helped Openscapes lead Open Science team trainings at NOAA Fisheries across all our science centers and involving 300+ staff. Since 2018, I have also been involved in teaching data science in India with the Indian National Centre for Ocean Information Services (INCOIS) and International Training Centre for Operational Oceanography (ITCOocean). In September 2023, I taught a course and hackweek at ITCOocean on using ocean remote-sensing data for fisheries management and research in the Indian Ocean and Bay of Bengal.

Most of my research is on GitHub and organized into the following organizations:

My big current projects are

My research is focused on stochastic processes and statistical models for complex multivariate, interacting systems. Much of what I do involves developing algorithms for fitting multivariate autoregressive state-space (MARSS) models to time-series data, which comes up in vector autoregressive state-space modeling, dynamic linear modeling, MAR(1) modeling, and dynamic factor analysis. I developed an EM algorithm for fitting a general constrained version of these models and develped the MARSS package for fitting such models. In my spare time, I’ve been working on predictive models of “multi-player” systems—I’ve been studying this with soccer match data. This is another application of my work on developing predictive models using ‘bad’ data.


  • Population Modeling
  • Statistical Ecology
  • Conservation Biology
  • Time-series Analysis
  • Stochastic Processes


  • PhD in Zoology, 1995, University of Washington
  • BS in Mechanical Engineering, 1988, Stanford University
  • BS in Biology, 1988, Stanford University