Niko Sarcevic
Nikolina “Niko” Šarčević is a cosmologist at Duke University working on cosmological inference and large-scale structure. She is a member of the LSST Dark Energy Science Collaboration (DESC) and the NASA Roman Space Telescope science collaborations. Her research focuses on statistical methods, astrophysical systematics, and scientific software for cosmology. Previously, she worked on dark matter searches as part of the XENON experiment.
Session
Many scientific workflows rely on derivatives of complex models: Fisher forecasts, sensitivity analysis, gradient-based inference, and emulator construction. In practice, these derivatives are often difficult to compute reliably and integrate into end-to-end inference pipelines.
DerivKit is an open-source Python toolkit that provides a unified framework for derivative-based scientific inference. It supports multiple derivative backends and connects model evaluation directly to downstream inference tools, including Fisher analyses and higher-order likelihood approximations. The framework also provides diagnostics and visualization tools for exploring parameter sensitivities and degeneracies.
Originally developed for cosmological forecasting pipelines, DerivKit is designed to be domain-agnostic and easily integrated into scientific Python workflows.