I am an independent research group leader at the Max Planck Institute for Intelligent Systems (MPI-IS)

My research background is in machine learning and algorithm design with a recent focus on developing fair and efficient ML models. More broadly, I study the interactions between humans and AI and use my findings to design AI systems that augment humans’ abilities rather than replacing them. I got my Ph.D. from the School of Computer Science at Georgia Tech. I was fortunate to work with Prof. Santosh Vempala. Here is my CV .

I am looking for Ph.D. students with a strong ML background. If you are interested to work with me, please apply to IMPRS-IS or CLS program (field of research "Machine Learning") and mention my name in the comment section. Deadline: Nov 2, 2020.


Socially Fair k-Means Clustering

Mehrdad Ghadiri, Samira Samadi, Santosh Vempala


Human Aspects of Machine Learning

Ph.D. thesis, Georgia Tech. [pdf]

A Human in the Loop is Not Enough: The Need for Human-Subject Experiments in Facial Recognition

Forough Poursabzi-Sangdeh, Samira Samadi, Jennifer Wortman Vaughan, and Hanna Wallach

Fair and Responsible AI workshop [CHI’20][pdf][Article by Georgia Tech][Article by biometricupdate.com]

Multi-Criteria Dimensionality Reduction with Applications to Fairness

Uthaipon Tantipongpipat, Samira Samadi, Mohit Singh, Jamie Morgenstern, and Santosh Vempala

Conference on Neural Information Processing Systems [NeurIPS'19 (spotlight)] [arXiv][Code][Press]

Guarantees for Spectral Clustering with Fairness Constraints

Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi, and Jamie Morgenstern

International Conference on Machine Learning [ICML'19][pdf][code][poster][press]

The Price of Fair PCA: One Extra Dimension

Samira Samadi, Uthaipon Tantipongpipat, Jamie Morgenstern, Mohit Singh, and Santosh Vempala

Conference on Neural Information Processing Systems [NeurIPS'18][pdf][code][press]

Usability of Humanly Computable Passwords

Samira Samadi, Santosh Vempala, and Adam Tauman Kalai

AAAI Conference on Human Computation and Crowdsourcing [HCOMP'18] [pdf][press]

Finding Meaningful Cluster Structure amidst Background Noise

Shrinu Kushagra, Samira Samadi, and Shai Ben-David.

Algorithmic Learning Theory [ALT'16] [pdf]

Near-Optimal Herding

Nicholas J. A. Harvey, and Samira Samadi

Conference on Learning Theory [COLT’14] [pdf][a blog post]

Professional Experience

Microsoft Research NYC, Spring 2019

Internship. Hosts: Jenn Wortman Vaughan and Hanna Wallach

Toyota Technological Institute at Chicago, Summer 2018

Internship. Host: Avrim Blum

Sentient Technologies, San Francisco, Summer 2016

Internship. Host: Phil Long


  • Co-organizer : Georgia Tech Grad Women @ College of Computing 2018 - 2020.

  • Student organizer: Georgia Tech Computer Science open house 2018.

  • Reviewer: ICML (top reviewer), NeurIPS, COLT, AISTATS, AAAI, IEEE Signal Processing Letters