Hi! I'm a PhD student in the Machine Learning Department at CMU where I am fortunate to be advised by Pradeep Ravikumar and Andrej Risteski. Before entering grad school I was a software engineer at Google NYC where I worked on Search Infrastructure. Before that I graduated from CMU with degrees in computer science and statistics & machine learning.
I'm broadly interested in the theoretical foundations of machine learning as a basis for human intelligence; in particular, I focus on robustness, representation learning, and out-of-distribution generalization. I work to develop principled formal analyses of the statistical and algorithmic properties of these tasks and possible approaches to solving them.
[Google Scholar] [CV]You can reach me at [firstname] at cmu.edu
The Risks of Invariant Risk Minimization
ICLR 2021 (To Appear)
(Also Appeared) NeurIPS 2020 Workshop: Causal Discovery & Causality-Inspired Machine Learning
Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski
[arXiv]
[CMU AI Seminar]
[2 minute spotlight presentation]
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing
ICML 2020
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, Zico Kolter
[arXiv]
[virtual poster/presentation]
[slides]
[blog post]
Certified Adversarial Robustness via Randomized Smoothing
ICML 2019
Jeremy Cohen, Elan Rosenfeld, Zico Kolter
[arXiv]
[code]
[short ICML talk]
[Zico's Simons Talk]
An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization
Under Review
(Short Version) ICLR 2021 Workshop: RobustML
Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski
[arXiv]
Self-Reflective Variational Autoencoder
ICLR 2021 Workshop: Hardware Aware Efficient Training
Ifigeneia Apostolopoulou, Elan Rosenfeld, Artur Dubrawski
[arXiv]
Human-Usable Password Schemas: Beyond Information-Theoretic Security
CMU Senior Thesis
Awarded “Exemplary Senior Honors Thesis”
Elan Rosenfeld, Santosh Vempala, Manuel Blum
[arXiv]
[poster]