Nick Boyd

Nick Boyd photo 

I'm a postdoc at the Broad Institute working with Aviv Regev. I got my PhD in Statistics under Michael Jordan and Ben Recht.


DeepLoco: Fast 3D Localization Microscopy Using Neural Networks. N. Boyd, E. Jonas, H. Babcock, B. Recht. Preprint. Code.

Saturating Splines and Feature Selection. N. Boyd, T. Hastie, S. Boyd, B. Recht, M. Jordan. JMLR. Code.

The Alternating Descent Conditional Gradient Method for Sparse Inverse Problems. N. Boyd, G. Schiebinger, B. Recht. SIAM J. Optim. 27(2), 616–639.

Also covered in my dissertation. ADCG won the 2016 SMLM 2D high-density challenge. For a simple demonstration of how to use ADCG, see this tutorial.

Streaming Variational Bayes. T. Broderick, N. Boyd, A. Wibisono, A. Wilson, M. Jordan. NIPS 2013.

Graph-Theoretic Topological Control of Biological Genetic Networks. A. Aswani, N. Boyd, C. Tomlin. ACC 2009.

Sets as Measures: Optimization and Machine Learning. N. Boyd. 2018.

My dissertation covers ADCG, saturating splines, and DeepLoco.


305 Evans Hall
Berkeley, CA 94704