Qingchen Wang
Welcome to my website!
I am Qingchen Wang, Assistant Professor in Innovation and Information Management at the University of Hong Kong. My research focuses on the development and application of machine learning and artificial intelligence techniques for solving real-life business problems.
Selected projects include data-driven driven consumer debt collection, revenue management for parking with advanced reservations, call center staffing and scheduling, and multi-channel conversion attribution. Some current topics include online labor markets, healthcare informatics, and last mile delivery. I also supervise MSc and MBA students in Business Analytics and Data Science.
To supplement my research I am a seasoned practitioner of machine learning and predictive analytics. I take part in predictive analytics competitions and have top finishes in a number of international competitions, earning the title of competition "Grandmasters" on Kaggle (currently one of only 130 among over 2,000,000 people worldwide).
Over the past three years I have taken part in over 30 competitions, having worked on predictive analytics problems for many companies including: Facebook, Walmart, Yelp, Airbnb, Telstra, Liberty Mutual, Expedia, Prudential, Home Depot, Allstate, Red Hat, BNP Paribas, Santander, Bosch, and Rossmann. The types of problems include: demand forecasting, customer marketing response, network fault severity, housing hazards, claims severity, restaurant inspection failures, shopping cart segmentation and many others.
I also worked as a Data Scientist for ORTEC B.V., where we developed data-driven algorithms for multi-channel conversion attribution, display banner advertising, and built a chatbot for a financial services firm.