I am an Assistant Professor of Electrical and Computer Engineering at UC Santa Barbara. My lab, the Geometric Intelligence Lab, aims to reveal the geometric signatures of natural and artificial intelligence. Before joining UCSB, I performed my postdoctoral work in Statistics at Stanford with Susan Holmes, and my doctoral work in Computer Science at Inria with Xavier Pennec.
Research
Interested? PhD and Postdoc positions are available in the Geometric Intelligence Lab! Explore the research areas and get in touch with us.
My methodological interests lie at the intersection of Geometry, Statistics and Computer Science.
Geometric Statistics: Statistical theory for data belonging to non-linear spaces, like metric spaces and Riemannian manifolds. Shape data, or weighted graph data naturally belong to such spaces, while high-dimensional data can be naturally projected to such spaces.
Dimensionality reduction in non-linear spaces: Fréchet mean, Submanifold learning in metric spaces and Riemannian manifolds, with a special interest for manifolds with additional properties, like Lie groups and Quotient spaces.
Fast implementation of the above techniques: Variational inference and variational autoencoders for submanifold learning.
Statistical properties of the above techniques: Asymptotic studies and bias-correction methods.
My application domains are neuroscience and neuroimaging, extracting knowledge from data such as:
Brain shapes, as observed in brain MRIs (macroscopic scale),
Brain BOLD (blood oxygen level dependent) activation, as observed in brain functional MRIs (macroscopic scale),
Brain structural and functional connectomes (macroscopic scale),
Neuronal electric signals, either from EEG or from deep brain implants (macroscopic or microscopic scale),
Beside my research interests, I am a lecturer for the classes “Introduction to Statistical Methods: Precalculus“ (2019) and “Statistical Methods for Engineering and the Physical Sciences“ (2018, 2019) at Stanford University. I am a reviewer for the scientific journals Journal of Mathematical Imaging and Vision JMLR (2015, 2017), Biometrika (2018) and the Journal of Mathematical Neuroscience (2019), as well as a reviewer for the conferences NeurIPS (2016, 2018, 2019), International Conference of Machine Learning ICML (2019), Geometric Science of Information GSI (2017, 2019). I am a member of the scientific committee of the Conference of Geometric Science of Information (GSI) (2017, 2019) and I was one of the two lead organizers of the workshop on Brain Computing at the Berkeley-Inria-Stanford annual meeting (2017).
You can follow me on: Github, LinkedIn, Twitter: @ninamiolane.