Curriculum Vitae
Education
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 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
Working Papers
- Data-driven Consumer Debt Collection via Machine Learning and Approximate Dynamic Programming, with Ruben van de Geer and Sandjai Bhulai
- SSRN link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3250755
- Under review at Management Science—Special Issue on Data-Driven Prescriptive Analytics
- Predicting Call Center Performance with Machine Learning, with Siqiao Li and Ger Koole
- Paper link: https://drive.google.com/open?id=1Ue2MjxHWmvyyXcMlnqKGA4NOOoDcnW9A
- Under review at the MSOM Practice Based Research Competition
- Multi-channel Conversion Attribution: A Machine Learning Approach, with Piet Pepperkorn and Maarten Soomer
- Manuscript in preparation; target journal: Management Science
- Revenue Management for Parking with Advanced Reservations, with Ruben van de Geer and Arnoud den Boer
- Manuscript in preparation; target journal: Management Science
Research in Progress
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
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
Teaching Experience
- Vrije University Amsterdam:
- 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
- University of Amsterdam:
- Master Thesis Supervision (MBA in Big Data Analytics), 2017 & 2018
- 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
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
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
- Led the research and development of multiple data science products internally and externally
- 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
Personal Information
- Citizenship: Canada
- Programming skills: Python, R, Matlab, Java, C++, C#, Haskell, Prolog
- Languages: English (Native), Mandarin (Fluent)