I am a fifth-year Ph.D. student in Computer Science at Stanford University, advised by Percy Liang. I am interested in fair, robust, and reliable machine learning. In the past, I have also worked on natural language processing.

Before joining Stanford I did my Masters at CSAIL MIT supervised by Martin Rinard and my B.Sc. in Computer Engineering at Sharif University of Technology.


Noise Induces Loss Discrepancy Across Groups for Linear Regression, Fereshte Khani, Percy Liang, International Conference in Machine Learning (ICML), 2020 [slides][code]

Maximum Weighted Loss Discrepancy, Fereshte Khani, Aditi Raghunathan, Percy Liang. Safe Machine Learning workshop at the International Conference on Learning Representation (ICLR), 2019. [slides][poster][code]

Planning, Inference, and Pragmatics in Sequential Language Games, Fereshte Khani, Noah D. Goodman, Percy Liang. Transactions of the Association for Computational Linguistics (TACL), 2018. [slides][code][dataset]

Unanimous prediction for 100% precision with application to learning semantic mappings, Fereshte Khani, Martin Rinard, Percy Liang. Association for Computational Linguistics (ACL), 2016. [poster][code]

Learning precise partial semantic mappings via linear algebra, Fereshte Khani. Master thesis, Massachusetts Institute of Technology, 2016.

 An algorithm for discovering clusters of different densities or shapes in noisy data sets, Fereshte Khani, Mohammad Javad Hosseini, Ahmad Ali Abin, Hamid Beigy. ACM Symposium on Applied Computing (ACM-SAC), 2013.




Address: G-256, Gates Computer Science, 353 Serra Mall, Stanford, CA 94305

Email: fereshte@stanford.edu