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I’m a second year PhD student in computer science at Cornell, where I am extremely fortunate to be advised by Jon Kleinberg. My main interests are in algorithms, network science, and machine learning. I am supported by an NDSEG fellowship.

Prior to coming to Cornell, I spent the 2018-2019 academic year at Google Research in the Discrete Algorithms Group. I hold a joint BS/MS degree in computer science from Stanford, where I was lucky to work with Greg Valiant.

### publications

Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels

Michela Meister, Tamás Sarlós, and David P. Woodruff

*Advances in Neural Information Processing Systems (NeurIPS) 2019*

[pdf]

A Data Prism: Semi-verified learning in the small-alpha regime

Michela Meister and Gregory Valiant

*Conference on Learning Theory (COLT) 2018*

[pdf][video]

### teaching

I served as a teaching assistant for the following Stanford courses:

- Optimization and Algorithmic Paradigms

(taught by Moses Charikar)
- Probability for Computer Scientists

(taught by Mehran Sahami, Chris Piech, and Will Munroe)
- Mathematical Foundations of Computing

(taught by Keith Schwarz)
- Mathematical Methods for Robotics, Vision, and Graphics

(taught by Justin Solomon and Doug James)