ANDREW ILYAS

I am a third-year PhD student at MIT, fortunate to be coadvised by Costis Daskalakis and Aleksander Madry. I recently graduated from MIT with a concurrent B.S./M.Eng, double majoring (for B.S.) in Computer Science and Math. I am supported by the Open Philanthropy AI Fellowship.

My M.Eng. thesis was supervised by Costis Daskalakis at MIT CSAIL. In the past, I've been a founding member of labsix, and have had the opportunity to work at the MIT CBMM, the Database Lab at MIT, and Two Sigma Labs.

Selected Papers

* denotes equal contribution

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Do Adversarially Robust ImageNet Models Transfer Better?
Hadi Salman*, Andrew Ilyas*, Logan Engstrom, Ashish Kapoor, Aleksander Madry (2020)
Blog Post, GitHub (Code and Models)
Oral presentation, NeurIPS 2020

Noise or Signal: The Role of Image Backgrounds in Object Recognition
Kai Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry (2020)
Blog Post

From ImageNet to Image Classification: Contextualizing Progress on Benchmarks
Dimitris Tsipras*, Shibani Santurkar*, Logan Engstrom, Andrew Ilyas, Aleksander Madry (2020)
Blog Post
ICML 2020

Identifying Statistical Bias in Dataset Replication
Logan Engstrom*, Andrew Ilyas*, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry (2020)
Blog Post
ICML 2020

Implementation Matters in Deep Policy Gradient Algorithms
Logan Engstrom*, Andrew Ilyas*, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry (2020)
Slides and video
Oral presentation, ICLR 2020

A Closer Look at Deep Policy Gradient Algorithms
Andrew Ilyas*, Logan Engstrom*, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry (2020)
Slides and video
Oral presentation, ICLR 2020

Image Synthesis with a Single (Robust) Classifier
Shibani Santurkar*, Dimitris Tsipras*, Brandon Tran*, Andrew Ilyas*, Logan Engstrom*, Aleksander Madry (2019)
NeurIPS 2019. Blog Post, Github

Adversarial Robustness as a Prior for Learned Representations
Logan Engstrom*, Andrew Ilyas*, Shibani Santurkar*, Dimitris Tsipras*, Brandon Tran*, Aleksander Madry (2019)
Blog Post, Github

Adversarial Examples are not Bugs, They are Features
Andrew Ilyas*, Shibani Santurkar*, Dimitris Tsipras*, Logan Engstrom*, Brandon Tran, Aleksander Madry (2019)
Blog Post, Datasets
Spotlight presentation, NeurIPS 2019

Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors
Andrew Ilyas*, Logan Engstrom*, Aleksander Madry
ICLR 2019. Github

How Does Batch Normalization Help Optimization?
Shibani Santurkar*, Dimitris Tsipras*, Andrew Ilyas*, Aleksander Madry
Blog Post, Video (3 minutes)
Oral presentation, NeurIPS 2018.

Black-box Adversarial Attacks with Limited Queries and Information
Andrew Ilyas*, Logan Engstrom*, Anish Athalye*, Jessy Lin*
ICML 2018. Partial-Information/GCV Blog Post, Label-Only Attack Blog Post, Github

Synthesizing Robust Adversarial Examples
Anish Athalye*, Logan Engstrom*, Andrew Ilyas*, Kevin Kwok
ICML 2018. Blog Post

Training GANs with Optimism
Constantinos Daskalakis*, Andrew Ilyas*, Vasilis Syrgkanis*, Haoyang Zeng*
ICLR 2018. Github

Extracting Syntactic Patterns From Databases
Andrew Ilyas, Joana M.F. da Trindade, Raul C. Fernandez, Samuel Madden
ICDE 2018. Github

MicroFilters: Harnessing Twitter for Disaster Managment
Andrew Ilyas
Chairman’s award winner, IEEE GHTC 2015.

Short Papers/Miscellanea

The robustness python library
GitHub repository/PyPI package. Documentation on ReadTheDocs

Evaluating and Understanding the Robustness of Adversarial Logit Pairing
Logan Engstrom*, Andrew Ilyas*, Anish Athalye* (2018)
NeurIPS Security in Machine Learning Workshop 2018

Personal projects (old stuff)

In this section I have included a list of previous hardware/software projects, including hackathon products, and weekend projects.

Really old stuff

In this section I have included a near-complete list of previous research topics, and links to the papers, reports, or products created as a result of that research. The projects are sorted chronologically, from 2009 to 2015.

Projects