- 2006 Ph.D. in Industrial Engineering, University of Washington, Seattle, WA
- 2003 Master of Science, Industrial Engineering, University of Washington, Seattle, WA
- 2002 Master of Science, Industrial Engineering, University of Tennessee, Knoxville, TN
- 1997 Bachelor of Engineering, Punjab Engineering College, India
Applications of Artificial Intelligence, Machine-Learning, and Econometrics on Digital Platforms, Information Systems, Healthcare
- 2018 – Present: Assistant Professor – MIS, School of Business, University of Washington Bothell
- 2015 – 2018: Assistant Professor, Department of Business Information and Technology (BIT), Fogelman College of Business and Economics, University of Memphis, Memphis, TN
- 2012 – 2015: Adjunct Faculty, Master of Healthcare Administration, Pacific University, Forest Grove, OR
2006 – 2015: Researcher/Analyst – Machine Learning and Big Data Analytics, Intel Corporation, USA
Machine-Learning for Business
Programming for Business
Statistics for Business
Digital Platform Analytics
SELECTED RESEARCH PUBLICATION
- Paruchuri, S., Pollock, T. and Kumar, N. 2019. “On the tip of the brain: Understanding when negative reputational events can have positive reputation spillovers, and for how long,” forthcoming in Strategic Management Journal (SMJ).
- Kumar, N., Qiu, L. and Kumar, S. 2018. “Exit, Voice, and Response in Digital Platforms: An Empirical Investigation of Online Management Response Strategies,” Information Systems Research, 29(4), 849-870.
- Media Coverage: “Is Online Management Responsiveness Good for Business?” Fox School News, October 16, 2017.
- Best Paper Nomination, Conference on Information Systems and Technology (CIST), 2017.
- Kumar, N., Venugopal, D., Qiu, L. and Kumar, S. 2018. “Detecting Review Manipulation on Online Platforms with Hierarchical Supervised Learning,” Journal of Management Information Systems, 35(1), 350-380.
- Kumar, N., Mastrangelo, C. and Montgomery, D. 2011. “Hierarchical Modeling using Generalized Linear Models,” Quality and Reliability Engineering International, 27(6): 835-42.
- Kumar, N., Kennedy, K., Gildersleeve, K., Abelson, R., Mastrangelo, C.M. and Montgomery, D.C. 2006. “A Review of Yield Modeling Techniques in Semiconductor Manufacturing,” International Journal of Production Research, 44(23): 5019-36.
- Kumar, N., Qiu, L. and Kumar, S. “A Hashtag is Worth a Thousand Words: An Empirical Investigation of Social Media Strategies in Trademarking Hashtags,” In revision for resubmission at Management Science.
- Kumar, N., Venugopal, D., Qiu, L. and Kumar, S. “Detecting Anomalous Online Reviewers: An Unsupervised Approach Using Mixture Models,” Submitted to Journal of Management Information Systems.
- Rezaee, Z. and Kumar, N. “Integration of Big Data Education into the Business Curriculum” (Work-In-Progress)
- Kumar, N. “Using Data Analytics Techniques to Evaluate Performance,” Book Chapter in Applying Quality Management in Healthcare: A Systems Approach, by Spath, Patrice L., Kelly, Diane L., 4th Edition, Health Administration Press. 2017, Pages 167-202.
- Mastrangelo, C., Kumar, N. and Forrest, D. “Hierarchical Modeling for Monitoring Defects,” Book Chapter in Frontiers in Statistical Quality Control by Lenz, Hans-Joachim; Wilrich, Peter-Theodor; Schmid, Wolfgang (Eds.), 1st Edition. January 2010, Pages 225-36.
- Mastrangelo, C. and Kumar, N. “Feedback Control,” Book Chapter in Encyclopedia of Statistics in Quality and Reliability. John Wiley and Sons, Ltd. March 2008.
- Microsoft Azure Research Award ($20,000.00 Credit) (Year 2017-2018)
- Securing Online Review Platforms: An Anomaly Detection Framework using Advanced Machine-Learning. Funded by the Cluster to Advance Cyber Security & Testing (CAST), FedEx Institute of Technology (FIT), University of Memphis. ($12,000 per year) (Years 2015-2016, 2017-2018, 2018-2019)
- Applications of Data Science Principles in Software Testing. Funded by the FedEx Corporation ($12,000 per year) (Years 2015-2016, 2017-2018)