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Shirley Ho

Shirley Ho is an American astrophysicist and machine learning expert, currently at the Center for Computational Astrophysics at Flatiron Institute in NYC and at the New York University and the Carnegie Mellon University. Ho also has visiting appointment at Princeton University.

A cited expert in cosmology, deep learning and its applications in astrophysics and data science, her interests include developing and deploying deep learning techniques to better understand our Universe, and other astrophysical phenomena.

She significantly contributed to the development of several fields, including: cosmic microwave background, cosmological models, dark energy, dark matter, spatial distribution of galaxies and quasars, Baryon Acoustic Oscillations, cosmological simulations and applications of machine learning to cosmology and astrophysics.

More recently, Shirley Ho is noted for her work in leading the early adoption of Artificial Intelligence in Astrophysics. In particular, her team at Carnegie Mellon University was the first to apply 3D convolutional neural network in astrophysics, the same team then accelerated astrophysical simulations with deep learning for the first time. Her current team at [https://www.simonsfoundation.org/flatiron/center-for-computational-astrophysics/ Center for Computational Astrophysics] and Princeton University is the first to combine symbolic regression and neural network to recover physical laws from observations directly. Her team also led the first development and deployment of deep learning accelerated simulation based inference framework for large spectroscopic surveys.

Her team further accelerated physical simulations ranging from fluid dynamics simulations to planetary dynamics simulations using modern deep learning techniques, and developed techniques in interpretable machine learning for science. Provided by Wikipedia