Nina Taft

Nina Taft is a Senior Staff Research Scientist at Google where she leads the Applied Privacy Research group. Prior to joining Google, Nina worked at Technicolor Research, Intel Labs Berkeley, Sprint Labs and SRI. She received her PhD from UC Berkeley. Over the years, she has worked in the fields of networking protocols, network traffic matrix estimation, Internet traffic modeling and prediction, intrusion detection, recommendation systems and privacy. Her current interests like in applications of machine learning for privacy, private data analytics, and user experience. She has been the chair or co-chair of the SIGCOMM, IMC and PAM conferences. (While some papers are listed here, see Google Scholar for a complete listing.)

Google Publications

Previous Publications


    Privacy Tradeoffs in Predictive Analytics

    Stratis Ioannidis, Andrea Montanari, Udi Weinsberg, Smriti Bhagat, Nadia Fawaz, Nina Taft

    Sigmetrics, ACM (2014)


    Recommending with an Agenda: Active Learning of Private Attributes using Matrix Factorization.

    Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, Nina Taft

    ACM Recommendation Systems (RecSys) (2014)


    Privacy Preserving Matrix Factorization

    Valeria Nikolaenko, Stratis Ioannidis, Udi Weinsberg, Marc Joye, Nina Taft, Dan Boneh

    20th ACM Conference on Computer and Communications Security (CCS) (2013)


    Privacy Preserving Ridge Regression on Hundreds of Millions of Records

    Valeria Nikolaenko, Udi Weinsberg, Stratis Ioannidis, Marc Joye, Dan Boneh, Nina Taft

    Symposium on Security and Privacy, IEEE (2013), pp. 334-348


    BlurMe: Inferring and Obfuscating User Gender Based on Ratings.

    Udi Weinsberg, Smriti Bhagat, Stratis Ioannidis, Nina Taft

    ACM Recommendation Systems (RecSys) (2012)


    CARE: Content Aware Redundancy Elimination for Challenged Networks

    Athula Balachandran, Gianluca Iannaccone, Nina Taft, Qingxi Li, Srinivasan Seshan, Udi Weinsberg, Vyas Sekar

    ACM Hot Topics in Networking (2012)


    Finding a Needle in a Haystack of Reviews: Cold Start Context-Based Hotel Recommender System

    Asher Levi, Osnat Mokryn, Christophe Diot, Nina Taft

    Proceedings of ACM Conference on Recommender Systerms (2012), pp. 115-122


    Public Health for the Internet (PHI)

    Joseph M. Hellerstein, Tyson Condie, Minos N. Garofalakis, Boon Thau Loo, Petros Maniatis, Timothy Roscoe, Nina Taft

    CIDR (2007), pp. 332-340


    Combining Filtering and Statistical Methods for Anomaly Detection

    Augustin Soule, Kave Salamatian, Nina Taft

    ACM IMC (Internet Measurement Conference) (2005)


    Traffic Matrices: Balancing Measurements, Inference and Modeling

    Augustin Soule, Anukool Lakhina, Nina Taft, Konstantina Papagiannaki, Kave Salamatian, Antonio Nucci, Mark Crovella, Christophe Diot

    ACM Sigmetrics: Conference on Measurement and Modeling of Computer Systems (2005)


    Structural Analysis of Network Traffic Flows

    Anukool Lakhina, Konstantina Papagiannaki, Mark Crovella, Christophe Diot, Eric Kolaczyk, Nina Taft

    ACM Sigmetrics: Conference on Measurement and Modeling of Computer Systems (2004), pp. 61-72


    Long Term Forecasting of Internet Backbone Traffic: Observations and Initial Models

    Konstantina Papagiannaki, Nina Taft, Zhi-Li Zhang, Christophe Diot

    IEEE Infocom (2003)


    Traffic Matrix Estimation: Existing Techniques and New Directions

    Alberto Medina, Nina Taft, Kave Salamatian, Supratik Bhattacharyya, Christophe Diot

    ACM Proceedings of SIGCOMM conference (2002), pp. 161-174