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Chris Volinsky

  • Clinical Professor of Technology, Operations, and Statistics

Joined Stern 2023

cv2309@stern.nyu.edu

Leonard N. Stern School of Business

Kaufman Management Center

44 West Fourth Street

New York, NY 10012

About Chris Volinsky

Chris Volinsky joined New York University Stern School of Business as a Clinical Professor of Technology, Operations, and Statistics in September 2023.

Volinsky’s career has focused on the analysis of large scale data sets in industry, and how companies use data to better serve customers, develop better products and services, forecast demand, and make processes more efficient. An important theme of this work is balancing the benefits of data science applications in business with increased regulatory policies and growing consumer concern with data privacy. His research interests include recommender systems, personalization, social network analysis, data visualization, and mitigating bias in machine learning models.

In 2009, Volinsky was a member of the seven-person, four-country team BellKor's Pragmatic Chaos that won a $1M prize in an open competition for improving Netflix's online recommendation system.

Prior to joining NYU Stern, Volinsky spent 25 years at AT&T, as part of AT&T Labs and the Chief Data Office. He led a team of 40 data scientists whose mission was to use the massive data sets generated by customers to solve unique and challenging problems and provide business impact across a global telecommunications and entertainment enterprise. Some memorable projects involved detecting internal employee fraud detection, applying computer vision models to drone videos of cell towers, and predicting customer care complaints. He enjoys the challenge of using real-world customer data to improve customer experience and increase business efficiency.

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  • Technology, Operations, and Statistics Department
  • Technology, Operations & Statistics
    • Artificial Intelligence
    • Data Mining
    • Data Science
    • Data Visualization
    • Statistics
    • Text Mining
  • PhD, Statistics

    University of Washington

  • BA, Statistics and Mathematics

    University of Buffalo