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
Data-driven Consumer Debt Collection via Machine Learning, with Ruben van de Geer and Sandjai Bhulai
Multi-channel Conversion Attribution: A Machine Learning Approach, with Piet Peeperkorn and Maarten Soomer
Predicting Call Center Performance with Machine Learning, with Siqiao Li and Ger Koole
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)