Curriculum Vitae

Academic Position

Assistant Professor of Information Systems, 2017-present
DO&IT Department, Robert H. Smith School of Business
University of Maryland, College Park


PhD in Information Systems, 2011 - 2017
NYU Stern School of Business, New York, NY
Committee: Foster Provost (chair), Arun Sundararajan, Daria Dzyabura, Patrick Perry

BS in Mathematical Sciences, 2003 - 2007
Worcester Polytechnic Institute, Worcester, MA

Research Interests

Data science, business analytics, design science, advertising, natural language processing, television, social media, crowdfunding


Journal Paper

  • Martens, D., Provost, F., Clark, J., and Junque De Fortuny, Enric (2016), ``Mining Massive Fine-Grained Behavior Data to Improve Predictive Analytics", MIS Quarterly 40, no 4. (2016). Designated European Research Paper of the Year by AIS and CIONET.

Papers Under Review

  • Clark, J. and Provost, F. (2016), ``Matrix-Factorization-Based Dimensionality Reduction in the Predictive Modeling Process: A Design Science Perspective."
  • Rhue, L. and Clark, J. (2016) ``Who Gets Started on Kickstarter? Racial Disparities in Fundraising Success."
  • Clark, J., Paiement, J.F., and Provost, F. (2016) ``Who's Watching TV?"

Work In Progress

  • ``Bayesian Transfer Multi-Instance Learning for Television Viewership", joint work with Jean-Francois Paiement and Foster Provost.

Conference Presentations

  • ``Bayesian Transfer Multi-Instance Logistic Regression"
    Workshop on Information Technologies and Systems  · Seoul, South Korea  · December, 2017
  • ``Big Data is Small Data"
    INFORMS Annual Meeting  · Houston, TX  · October, 2017
  • ``Recruiting Members of Underrepresented Groups: What Women-in-Tech Meetups do Differently"
    INFORMS Annual Meeting  · Houston, TX  · October, 2017
  • ``Using Dimensionality Reduction for Binary Classification on Massive, Sparse Data: Design Science Experiments and Guidelines"
    Conference on Information Systems and Technology  · Houston, TX  · October, 2017
  • ``Who's Watching TV?" (Poster)
    Conference on Information Systems & Technology  · Nashville, TN  · November, 2016
  • ``The Role of Dimensionality Reduction in Binary Classification for Social Data"
    INFORMS Annual Meeting  · Nashville, TN  · November, 2016
  • ``Who Gets Started on Kickstarter? Demographic Variation in Crowdfunding Success Rates"
    INFORMS Annual Meeting  · Nashville, TN  · November, 2016
  • ``Who's Watching TV?" (Poster)
    Workshop on Information in Networks  · New York NY  · October, 2015 
  • ``Predictive Modeling with Fine-Grained Behavior Data Using Dimensionality Reduction"
    Winter Conference in Business Intelligence  · Snowbird, Utah  · February, 2013
  • ``Portfolio Optimization with Non-smooth Constraints" (Poster)
    Nebraska Conference for Undergraduate Women in Mathematics  · Lincoln, NE  · February, 2006

Teaching Experience

  • Instructor, "Data Mining for Business Analytics"
    NYU Stern undergraduate course, Spring 2015 semester.
    Rating: 6.0/7 (38 total students)

  • Teaching Fellow, "Data Mining for Business Analytics"
    NYU Stern MS in Business Analytics, Summer 2016. Rating: 6.36/7
    NYU Stern MBA course, Spring 2012, Fall 2013, Spring 2014
    NYU MS in Data Science, Fall 2013

  • Peer Learning Assistant, Calculus and Linear Algebra
    Worcester Polytechnic Institute undergraduate courses, 2004-2007

Academic Activities & Service

  • Session chair
    Social Media Analytics track · INFORMS Annual Meeting 2017
  • Reviewer
    Machine Learning Journal, ICIS, CIST
  • Professional memberships: AIS, INFORMS
  • New York University  · All-University Graduate Commission  · 2013-2014
    Review and vote on proposals for new graduate programs at NYU
  • Carnegie Mellon University  · Summer Undergraduate Applied Mathematics Institute  · 2006
    Completed research project in calculus of variations
  • National Science Foundation  · Division of Undergraduate Research  · 2006
    Interactive Qualifying Project
  • Worcester Polytechnic Institute  · REU in Industrial Mathematics and Statistics  · 2005
    Completed research project in portfolio optimization with nonlinear, non-smooth constraints.

Professional Experience

  • AT&T Research, Florham Park, NJ
    Intern, June-August 2013
    Research internship developing unsupervised machine learning models to predict which member of a household is watching TV
    •  Implemented non-negative matrix factorization of digital cable channel viewership, decomposing each household's viewership into component parts, each associated with distinct demographics. G
    • Generated more intuitive targeting by associating resultant factors with aggregate demographic segments.
    • Developing deep-learning neural network to further improve targeting.
  • IMPAQT, Pittsburgh, PA
    Senior Decision Support Analyst, 2009-2011
    Decision Support Analyst, 2007-2009
    Performed statistical R&D to improve effectiveness of clients' online advertising at a search engine marketing agency.  Led projects and interfaced with clients.
    • Developed algorithms to optimize paid search campaigns' ROI through automated bid and budget management.
    • Provided data-driven support for Fortune 1000 clients in retail, consumer packaged goods, financial services, telecommunications, and automotive industries.
    • Completed ad-hoc statistical projects including estimating the relationship between paid search and television ads, the effect of search engine optimization in the context of other advertising efforts, and the impact of paid search ads on organic site traffic.

Programming Skills

  • Python
  • MatLab
  • Lua/Torch
  • SAS
  • SQL
  • Java