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, 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. Andrew Ilyas*, Logan Engstrom*, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, and Aleksander Mądry. Are Deep Policy Gradient Algorithms Policy Gradient Algorithms?. 2018.

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

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

  4. Logan Engstrom*, Andrew Ilyas*, and Anish Athalye*. Evaluating and Understanding the Robustness of Adversarial Logit Pairing. 2018.

* indicates equal contribution