My research interests include the design and analysis of algorithms, computational geometry, data mining and machine learning, and the application of such algorithms to interdisciplinary data.
I'm interested in understanding how data mining and machine learning algorithms could be unfair and what can be done to prevent that. I'm working with Suresh Venkatasubramanian and Carlos Scheidegger on examining this question in the context of the legal notion of disparate impact. I'm a 2015 - 2016 Fellow at the Data & Society Research Institute and have received a Knight News Challenge Prototype Fund grant for this work.
For more information, see fairness.haverford.edu.
Knight News Challenge Prototype Fund (2016): Could your data discriminate? Sorelle Friedler, Wilneida Negron, Surya Mattu, Suresh Venkatasubramanian. $35,000.
Data & Society Research Institute Fellow (2015 - 2016): Preventing Discrimination in Machine Learning: from theory to law and policy. $10,000.
The Dark Reactions Project aims to predict the results of chemical reactions from historical lab data and recommend future successful experiments. I'm working with chemists Josh Schrier and Alex Norquist on this project and we have received an NSF grant for this work.
For more information, see darkreactions.haverford.edu
NSF DMR-1307801 (2013 - 2016): The Dark Reaction Project: a machine learning approach to materials discovery. Joshua Schrier, Alexander Norquist, and Sorelle Friedler. $299,998.
I'm interested in understanding motion from a computational geometry and information theoretic point of view; creating frameworks and analyses that are theoretically sound and yet practically relevant. I'm working with Dianna Xu and Betul Atalay on related ideas for practical frameworks for kinetic data.
Paul Raccuglia, Katherine C. Elbert, Philip D. F. Adler, Casey Falk, Malia B. Wenny, Aurelio Mollo, Matthias Zeller, Sorelle A. Friedler, Joshua Schrier, and Alexander J. Norquist. Machine-learning-assisted materials discovery using failed experiments. Nature, 533: 73 - 76, May 5, 2016. [link]
Sorelle A. Friedler and David M. Mount. A Sensor-Based Framework for Kinetic Data Compression. Computational Geometry: Theory and Applications, 48(3): 147 - 168, March 2015. (doi: 10.1016/j.comgeo.2014.09.002) [PDF | link]
Sorelle A. Friedler and David M. Mount. Approximation algorithm for the kinetic robust k-center problem. Computational Geometry: Theory and Applications, 2010. (doi: 10.1016/j.comgeo.2010.01.001). [PDF (preprint) | link]
Sorelle A. Friedler, Yee Lin Tan, Nir J. Peer, and Ben Shneiderman. Enabling teachers to explore grade patterns to identify individual needs and promote fairer student assessment. Computers & Education, 51(4):1467-1485, December 2008. [PDF (preprint) | link] [code and help videos]
Michael Feldman, Sorelle A. Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian. Certifying and Removing Disparate Impact. Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015. [PDF]
Sorelle A. Friedler and David M. Mount. Spatio-temporal range searching over compressed kinetic sensor data. In Proc. of the European Symposium on Algorithms (ESA), pages 386-397, 2010. [PDF (preprint) | link] [TR]
2nd Workshop on Massive Data Algorithmics, 2010 [PDF]
Fall Workshop on Computational Geometry, 2009 [PDF]
Sorelle A. Friedler and David M. Mount. Compressing kinetic data from sensor networks. In Proc. of the 5th International Workshop on Algorithmic Aspects of Wireless Sensor Networks (AlgoSensors), pages 191 - 202, 2009. [PDF (preprint) | link] [TR]
Ifeoma Ajunwa, Sorelle Friedler, Carlos E. Scheidegger, and Suresh Venkatasubramanian. Hiring by Algorithm: Predicting and Preventing Disparate Impact. Presented at the Yale Law School Information Society Project conference Unlocking the Black Box: The Promise and Limits of Algorithmic Accountability in the Professions, Apr. 2, 2016. [PDF]
Philip Adler, Casey Falk, Sorelle A. Friedler, Gabriel Rybeck, Carlos Scheidegger, Brandon Smith, Suresh Venkatasubramanian. Auditing Black-box Models by Obscuring Features. arXiv:1602.07043. [link]
Michael Feldman, Sorelle A. Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian. Certifying and Removing Disparate Impact. Presented at the Fairness, Accountability, and Transparency in Machine Learning Workshop, Dec. 12, 2014. [link]
F. Betul Atalay, Sorelle A. Friedler, and Dianna Xu. Probabilistic Kinetic Data Structures. Presented at the Fall Workshop on Computational Geometry, Oct. 25, 2013. [PDF | link]
Sorelle A. Friedler and David M. Mount. Realistic compression of kinetic sensor data. Technical Report CS-TR-4959, University of Maryland, College Park, 2010. [PDF | TR]
Sorelle A. Friedler. Geometric Algorithms for Objects in Motion. Dissertation committee: Prof. David Mount (chair), Prof. William Gasarch, Prof. Samir Khuller, Prof. Steven Selden, Prof. Amitabh Varshney. Defense date: July 30, 2010. [PDF] [presentation]
As part of the indoor location team within Google X, I helped to use and develop applied machine learning techniques to implement an indoor location determination system running within Google Maps for Mobile on Android. The blog post announcing our launch can be found here.
When trying to locate a person inside a building using only a cell phone, GPS cannot be relied upon and so other phone sensors must be used instead. These sensors were not designed to be used for location purposes and measurements collected by them tend to be very noisy. These issues combine to create a hard machine learning problem that can be solved by making use of probabilistic graphical models and sensor fusion to locate a person indoors.
Mohammed Waleed Kadous, Isaac Richard Taylor, Cedric Dupont, Brian Patrick Williams, Sorelle Alaina Friedler. Permissions based on wireless network data. US 20130244684 A1. Publication date: Sep. 19, 2013.
Sorelle Alaina Friedler, Mohammed Waleed Kadous, Andrew Lookingbill. Position indication controls for device locations. US 20130131973 A1 (also WO 2013078125 A1). Publication date: May 23, 2013.