Curriculum Vitae

Education

  • 2019 (expected) Ph.D. in Data Science and Business Analytics, University of Amsterdam, Amsterdam, Netherlands
  • 2015 M.S. in Management, INSEAD, Fontainebleau, France
  • 2012 M.S. in Machine Learning, University College London, London, United Kingdom
  • 2011 B.S. in Computer Science and Biology, University of British Columbia, Vancouver, Canada

Research and Teaching Interests

  • Research:
      • Interface between machine learning and operations management
      • Data-driven optimization through predictive analytics
      • Innovative applications of data-driven optimization to business practice
  • Teaching:
      • Predictive analytics for business, applied machine learning, data wrangling
      • Area of specialization: Business Analytics and Data Science

Working Papers

Research in Progress

  • Optimizing Long-term Job Matching for an Online Marketplace, with Ashish Kabra
  • Data-driven Fatigue Management for Multiple Sclerosis Patients
  • Dynamic Optimization of Email Promotional Campaigns
  • Social Media Bot Detection with Machine Learning, with Juan Echeverria
  • Improving Display Advertising with Predictive Device Matching, with Taco Wijnsma

Other Peer-reviewed Publications

  • Li, S., Wang, Q., and Koole, G., Predicting Call Center Performance with Machine Learning, Proceedings of the INFORMS International Conference on Service Science, 2018.
  • Puterman, M. L. and Wang, Q., Optimal Design of the PGA Tour; Relegation and Promotion in Golf, Proceedings of MIT Sloan Sports Analytics Conference, 2011.
  • Puterman, M. L. and Wang, Q., Optimal Dynamic Clustering Through Relegation and Promotion: How to Design a Competitive Sports League, Quantitative Analysis in Sports, 7, issue 2, Article 7, 2010.

Teaching Experience

  • Vrije University Amsterdam:
    • Project Big Data (BS in Business Analytics), Instructor, 2019
    • Research Seminar in Business Analytics (MS in Business Analytics), Instructor, 2019
    • Data Wrangling (MS in Business Analytics), Instructor, 2019
    • Advanced Machine Learning (MS in Business Analytics), Teaching Assistant, 2018
    • Master Thesis Supervision (MS in Business Analytics), 2018 & 2019
  • University of Amsterdam:
    • Master Thesis Supervision (MBA in Big Data Analytics), 2017 & 2018 & 2019
    • System Optimization (MBA in Big Data Analytics), Teaching Assistant, 2016 & 2017
    • Statistics, Simulation, and Optimization (MS in Data Science), Teaching Assistant, 2017

Honors and Awards

  • Kaggle Grandmaster (only 122 worldwide out of 2,000,000+ people), 2016 - present
  • First place winner: Data Science Challenge Growing Instability competition, £20,000 prize, 2017
  • Second place winner: Home Depot Product Search Relevance competition, $12,000 prize, 2016
  • First place winner: Liberty Mutual Group Property Inspection Prediction competition, $12,000 prize, 2015
  • Second place winner: Yelp! Keeping It Fresh Restaurant Inspection Prediction competition, $1,000 prize 2015
  • INSEAD Ph.D. Scholarship, 2013 - 2014

Professional Experience

  • Data Scientist, ORTEC B.V., Amsterdam, Netherlands, 2015 - 2018
      • Led the research and development of multiple data science products internally and externally
          • Predictive cross device matching
          • Developing chat-bot for expert advice
          • Improving real-time bidding algorithm
          • Machine learning for revenue optimization
          • Digital media budget optimization
          • Multi-channel conversion attribution
  • Software Engineer intern, Blackberry, Kanata, Canada 2010
      • Core engineer on the Blackberry Facebook Application development team
  • Software Engineer intern, EA Sports, Burnaby, Canada 2009
      • Core engineer on the NCAA Basketball 10 development team

Personal Information

    • Citizenship: Canada
    • Programming skills: Python, R, Matlab, Java, C++, C#, Haskell, Prolog
    • Languages: English (Native), Mandarin (Fluent)