Curriculum Vitae

Employment

  • 2019 Assistant Professor in Innovation and Information Management, The University of Hong Kong, Hong Kong S.A.R.

Education

  • 2019 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: Data-driven prescriptive analytics, online labor markets, healthcare informatics
  • Teaching: Data analytics, predictive analytics, applied machine learning

Working Papers

Research in Progress

  • Hiring in online labor markets: The role of job-specific experience, with Ashish Kabra
  • What if you don’t surge price? The case of non-Uber like marketplaces, with Ashish Kabra
  • A prescriptive approach to improve home delivery success, with Stanley Lim
  • Robust recommender systems under cookie churn and cross-device browsing behavior
  • Cardiovascular disease prediction via machine learning
  • Pricing of reservations using machine learning

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

  • University of Hong Kong:
    • Business Data Analysis (MBA), Instructor, 2019-2020
  • 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

Personal Information

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