Dimitris Tsipras


I am a research scientist at OpenAI.

Before that, I was a postdoc at Stanford CS, mentored by Percy Liang and Greg Valiant, working on LLMs and in-context learning.

I did my PhD in CS at MIT with Aleksander Mądry, working on optimization and ML robustness.

I got my undergrad degree in ECE from NTUA, Greece, where I did my diploma thesis with Dimitris Fotakis.

my face

Selected papers Show all Show selected
(* means equal contribution)


Holistic Evaluation of Language Models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
TMLR 2023
website, code

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
Shivam Garg*, Dimitris Tsipras*, Percy Liang, Gregory Valiant
NeurIPS 2022
code

Editing a Classifier by Rewriting Its Prediction Rules
Shibani Santurkar*, Dimitris Tsipras*, Mahi Elango, David Bau, Antonio Torralba, Aleksander Mądry
NeurIPS 2021
blog post, code

Combining Diverse Feature Priors
Saachi Jain*, Dimitris Tsipras*, Aleksander Mądry
ICML 2022
blog post, code

Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses
Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein
TPAMI 2022

BREEDS: Benchmarks for Subpopulation Shift
Shibani Santurkar*, Dimitris Tsipras*, Aleksander Mądry
ICLR 2021
blog post, benchmarks

From ImageNet to Image Classification: Contextualizing Progress on Benchmarks
Dimitris Tsipras*, Shibani Santurkar*, Logan Engstrom, Andrew Ilyas, Aleksander Mądry
ICML 2020
blog post, ImageNet annotations

Identifying Statistical Bias in Dataset Replication
Logan Engstrom*, Andrew Ilyas*, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Mądry
ICML 2020
blog post, code

Image Synthesis with a Single (Robust) Classifier
Shibani Santurkar*, Dimitris Tsipras*, Brandon Tran*, Andrew Ilyas*, Logan Engstrom*, Aleksander Mądry
NeurIPS 2019
blog post, code/notebooks, demo

Learning Perceptually-Aligned Representations via Adversarial Robustness
Logan Engstrom*, Andrew Ilyas*, Shibani Santurkar*, Dimitris Tsipras*, Brandon Tran*, Aleksander Mądry
blog post, code/notebooks

Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas*, Shibani Santurkar*, Dimitris Tsipras*, Logan Engstrom*, Brandon Tran, Aleksander Mądry
NeurIPS 2019
blog post, datasets

On Evaluating Adversarial Robustness
Nicholas Carlini, Anish Athalye, Nicolas Papernot, Wieland Brendel, Jonas Rauber, Dimitris Tsipras, Ian Goodfellow, Aleksander Mądry, Alexey Kurakin

Label-Consistent Backdoor Attacks
Alexander Turner, Dimitris Tsipras, Aleksander Mądry

A Closer Look at Deep Policy Gradients
Andrew Ilyas*, Logan Engstrom*, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Mądry
ICLR 2020
blog post: part 1, part 2, part 3

Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO
Logan Engstrom*, Andrew Ilyas*, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Mądry
ICLR 2020
code

Robustness May Be at Odds with Accuracy
Dimitris Tsipras*, Shibani Santurkar*, Logan Engstrom*, Alexander Turner, Aleksander Mądry
ICLR 2019

How Does Batch Normalization Help Optimization?
Shibani Santurkar*, Dimitris Tsipras*, Andrew Ilyas*, Aleksander Mądry
NeurIPS 2018
blog post, 3-minute video

Adversarially Robust Generalization Requires More Data
Ludwig Schmidt, Shibani Santurkar, Dimitris Tsipras, Kunal Talwar, Aleksander Mądry
NeurIPS 2018

Exploring the Landscape of Spatial Robustness
Logan Engstrom*, Brandon Tran*, Dimitris Tsipras*, Ludwig Schmidt, Aleksander Mądry
ICML 2019
code

Towards Deep Learning Models Resistant to Adversarial Attacks
(α-β order) Aleksander Mądry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu
ICLR 2018
blog post: part 1 and part 2, MNIST Challenge, CIFAR10 Challenge

Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods
(α-β order) Michael B. Cohen, Aleksander Mądry, Dimitris Tsipras, Adrian Vladu
FOCS 2017

Efficient Money Burning in General Domains
(α-β order) Dimitris Fotakis, Dimitris Tsipras, Christos Tzamos, Manolis Zampetakis
SAGT 2015
Invited to special issue of Theory of Computing Systems