Hi, I am a research engineer at Apple working on machine learning. My email is: [first name] + [last name] + 14 at gmail dot com.
Bio
I received my PhD from Princeton University in 2019 doing research in meta-learning. I attended University of Wisconsin-Madison as an undergraduate and received a B.S. in Computer Science and a B.S. in Mathematics in 2012. In the past I have done internships at Amazon and Twitter Cortex. My CV can be found here.
Research
My research interests are in deep learning and its applications in computer vision and natural language processing.
Papers
CONFERENCE PAPERS
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Amortized Bayesian Meta-Learning
International Conference on Learning Representations (ICLR), 2019
[pdf] -
Meta Learning for Semi-Supervised Few-Shot Classification
International Conference on Learning Representations (ICLR), 2018
[pdf] -
Optimization as a Model for Few-Shot Learning
International Conference on Learning Representations (ICLR), 2017 [Oral Presentation]
[pdf] [code]
WORKSHOP PAPERS & PRE-PRINTS
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Amortized Bayesian Meta-Learning
NeurIPS Workshop on Meta-Learning, 2018
[pdf] -
Meta Learning for Batch Mode Active Learning
International Conference on Learning Representations (ICLR) Workshop, 2018
[pdf] -
Learning the Dimensionality of Word Embeddings
[pdf] [code]
Talks
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Optimization as a Model for Few-Shot Learning
International Conference on Learning Representations (ICLR). Toulon, France. May 2017.
[slides] [video]
Teaching
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Assistant Instructor, Princeton University
COS 424, Interacting with Data : Spring 2014
Advanced undergraduate course focusing on analyzing complex data sets using techniques from machine learning. -
Assistant Instructor, Princeton University
COS 423, Theory of Algorithms : Spring 2013
Advanced undergraduate course involving the design and analysis of efficient data structure and algorithms. -
Assistant Instructor, Princeton University
COS 126, General Computer Science : Fall 2012, Fall 2013
Course which introduces students to programming in Java and important concepts in computer science.