Photo of Logan Engstrom

Logan Engstrom

GitHub: @lengstrom
Google Scholar: here
CV/Resume: here


I'm a third year undergraduate at MIT studying Computer Science. I'm most interested in machine learning, optimization, and statistics. I currently work with Aleksander Mądry at MIT. This summer I am interning at Two Sigma; I previously interned at Google Brain (summer 2017) and Apple (summer 2016).

At MIT I play for the Simmons intramural soccer team and the Baker intramural dodgeball team. I used to organize HackMIT and help out in USAGE, the undergraduate advisory board for MIT EECS.


  1. Anish Athalye*, Logan Engstrom*, Andrew Ilyas*, and Kevin Kwok. Synthesizing Robust Adversarial Examples. ICML 2018, 2017.

  2. Andrew Ilyas*, Logan Engstrom*, Anish Athalye*, and Jessy Lin*. Black-box Adversarial Attacks with Limited Queries and Information. ICML 2018, 2017.

  3. Logan Engstrom*, Dimitris Tsipras*, Ludwig Schmidt, and Aleksander Mądry. A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations. NIPS Machine Learning and Computer Security Workshop, in review at NIPS 2018, 2018.

  4. Daniel Kang, Richard Sherwood, Amira Barkal, Tatsunori Hashimoto, Logan Engstrom, and David Gifford. Dnase-capture Reveals Differential Transcription Factor Binding modalities. PloS one, 2017.

* indicates equal contribution


  1. Dimitris Tsipras*, Shibani Santurkar*, Logan Engstrom*, Alexander Turner, and Aleksander Mądry. There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits). In review at NIPS 2018, 2018.

  2. Andrew Ilyas*, Logan Engstrom*, Ludwig Schmidt, and Aleksander Mądry. Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors. In review at NIPS 2018, 2018.

* indicates equal contribution