I'm a Research Professor of Astronomy at the California Institute of Technology and the Project Scientist for the Zwicky Transient Facility (ZTF), the first of a next generation of time-domain sky surveys producing hundreds of thousands of public transient alerts per night.

My work has primarily been in the emerging discipline of astroinformatics, which combines astronomy, applied computer science, and statistics. I have previously worked on the Catalina Real-time Transient Survey (CRTS), a still unmatched data set in terms of temporal baseline coverage; the NOAO DataLab; the Virtual Observatory; and the Palomar-Quest Digital Sky Survey. My work focuses on the statistical characterization of variability and extreme quasar variability and the development of infrastructure and algorithms for real-time alert stream inferencing.

I have also worked with semantic technologies and machine learning to catalog software and with neuroscience and genomics groups at Caltech and USC on smart data management to support their research and novel analysis algorithms.

I have ongoing projects in real-time low latency inferencing via the NSF-funded HDR Institute for Accelerated AI Algorithms for Data-Driven Discovert (A3D3), the application of reinforcement learning to optimize followup campaigns of astrophysical phenomena, the development of neural differential models for modeling the variability of supermassive black holes, and the functional analysis modeling of multivariate time series.