I am currently a third year CS PhD student at the University of Washington advised by Ali Farhadi. Before coming to Seattle, I received my bachelor's in math (minor in physics and CS) and an MS in CS from Cornell University where I was advised by Bharath Hariharan.

Broadly my research is in computer vision and machine learning. Currently I am interested in transfer learning and learning from limited supervision.

Publications

[CVPR '22] Task Adaptive Parameter Sharing for Multi-Task Learning
Matthew Wallingford, Hao Li, Alessandro Achille, Avinash Ravichandran, Charless Fowlkes, Rahul Bhotika, Stefano Soatto
Conference on Computer Vision and Pattern Recognition (CVPR) 2022

[NeurIPS '21] LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes
Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham Kakade, Ali Farhadi
Neural Information Processing Systems (NeurIPS) 2021

[Preprint] FLUID: A Unified Evaluation Framework for Flexible Sequential Data
Matthew Wallingford, Aditya Kusupati, Keivan Alizadeh-Vahid, Aaron Walsman, Aniruddha Kembhavi, Ali Farhadi

[CVPR '20] RoboTHOR: An Open Simulation-to-Real Embodied AI Platform
Matt Deitke, Winson Han, Alvaro Herrasti, Aniruddha Kembhavi, Eric Kolve, Roozbeh Mottaghi, Jordi Salvador, Dustin Schwenk, Eli VanderBilt, Matthew Wallingford, Luca Weihs, Mark Yatskar, Ali Farhadi
Conference on Computer Vision and Pattern Recognition (CVPR) 2020