Curriculum Vitae

Education

PhD in Information Systems, 2011 - 2017 (Expected)
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


Research

Journal Paper

  • Martens, D., Provost, F., Clark, J., and Junque De Fortuny, Enric (2016), ``Mining Massive Fine-Grained Behavior Data to Improve Predictive Analytics", Forthcoming in Management Information Systems Quarterly.

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

  • ``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

  • 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.

Awards & Honors

  • Worcester Polytechnic Institute  · Graduated with Highest Honors  · 2007
    Provost's Major Qualifying Award in Mathematical Sciences
    Senior Math Award
  • Consortium for Mathematics and its Applications Mathematical Contest in Modeling  · 2005
    Meritorious Award

Work 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.

Selected Coursework

Course Title Instructor NYU Department
Microeconomics Roy Radner Stern Econ
Technical Foundations of IS Alex Tuzhilin Stern IS
Research Seminar: IT and Organizations Natalia Levina Stern IS
Behavioral Research Methods Lyle Brenner Stern PhD Interarea
Research Seminar: Digital Economics Arun Sundararajan Stern IS
Research Seminar: Data Science Foster Provost Stern IS
Econometrics William Greene Stern Econ
Machine Learning Yann LeCun Courant CS
Statistical Natural Language Processing Slav Petrov Courant CS/Google
Big Data Yann LeCun, John Langford Courant CS, Microsoft Research
Strategy Kei Kuwai Stern Econ
Honors Algorithms Chee Yap Courant CS
Probabilistic Graphical Models David Sontag Courant CS

Programming Skills

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