No one likes to hear “computer says no”. But there may be more ways to be transparent about algorithm-driven rejections than...
Pavel Kireyev is an Assistant Professor of Marketing at INSEAD. He conducts research with data-driven companies and studies innovative marketing technologies, platforms, and marketplaces. Prior to joining INSEAD, he led projects on the development of machine learning algorithms at a startup, formed partnerships with corporate artificial intelligence labs, and worked as a data scientist with large organizations in the US and Japan.
Pavel uses modern quantitative methods to uncover how organizations can effectively coordinate their pricing and advertising strategies across multiple platforms, benefit from new resources such as crowd intelligence, and manage behavioral data to improve decision-making and market design in multi-sided marketplaces. He has published research in academic journals on quantitative marketing and presented at several business schools and international conferences. He holds a Doctorate in Business Administration from the Harvard Business School, an MA in Statistics from Yale University, and a BSc in Business Mathematics and Statistics from the London School of Economics.
Your prize money goes further when it’s distributed among a larger group of winners.
For Preferred Networks, building tech for self-driving cars and smart factories is the daily routine. One of its biggest...
AI and machine learning are changing global consumption habits, and companies are playing catch-up.