Welcome to my website!
I will be joining the University of Hong Kong as an Assistant Professor in Innovation and Information Management starting in Fall 2019.
I am Qingchen Wang, a Ph.D. candidate at the Amsterdam Business School of the University of Amsterdam. My research focuses on the development of data-driven optimization methodologies by leveraging advanced machine learning techniques. I am also heavily involved in practice-driven research as all of my projects originate from existing business challenges and I work with industry collaborators to identify innovative solutions and validate our solutions with controlled field experiments.
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. I also supervise MSc and MBA students in Business Analytics on their theses and assist with teaching the Advanced Machine Learning and Data Wrangling courses.
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 122 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.