Mark Ibrahim

SOFTWARE ENGINEER | NEW YORK CITY, UNITED STATES

How do we encode our intuitive ability to recognize the same dog while it's jumping during the day or hiding behind a tree at night? Mark is interested in building representations of the factors of variation in the world around us. Mark is exploring how tools from areas such as topology, group theory, and equivariant architectures can shed light on how representations can improve interpretability, robustness, and data-efficiency (semi- or self-supervised settings).

Mark's Work

Mark's Publications

November 09, 2021

COMPUTER VISION

CORE MACHINE LEARNING

Grounding inductive biases in natural images: invariance stems from variations in data

Diane Bouchacourt, Mark Ibrahim, Ari Morcos

November 09, 2021

October 18, 2021

CORE MACHINE LEARNING

CrypTen: Secure Multi-Party Computation Meets Machine Learning

Brian Knott, Shobha Venkataraman, Awni Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten

October 18, 2021

September 23, 2020

ML APPLICATIONS

Neural Relational Autoregression for High-Resolution COVID-19 Forecasting

Maximilian Nickel, Levent Sagun, Mark Ibrahim, Matt Le, Timothee Lacroix

September 23, 2020