I develop and implement statistical and numerical methods for scientific computing and machine learning and turn them into reliable open-source software.
Currently I work at the ML ⇌ Science Colaboratory at the University of Tübingen. I hold a PhD in Biological and Medical Informatics from UCSF, and my work spans probabilistic modeling, scientific software, and computational methods across several applied domains.
I'm currently exploring industry roles where I can combine research, probabilistic machine learning, and software engineering.
To get a taste of the kinds of problems I've tackled, see selected projects →
Machine Learning Research Engineer, ML ⇌ Science Colaboratory, University of Tübingen (2021–present) Research and software engineering at the interface of machine learning, statistics, numerical computation, and scientific applications.
Postdoctoral Researcher, UCSF (2020–2021)
Systems Analyst, DOE Joint Genome Institute (2009–2014)
I occasionally write about mathematical derivations, statistical computation, and problems that arise while developing scientific software. See my technical writing.
I was also a guest on the Learning Bayesian Statistics podcast: Bayesian Computational Biology in Julia, with Seth Axen.