Ke Li (INSEAD)

Hello, my name is Ke Li (李可). I am currently a PhD student in Decision Sciences at INSEAD, fortunate to be advised by Spyros Zoumpoulis.

I pursue two distinct but complementary research areas at the intersection of AI, management, and decision sciences.

One stream of my research develops decision-aware learning methods for managerial decision-making. I study how firms can design learning systems that optimize not only predictive accuracy, but also the quality of the downstream decisions they support. My current work applies this perspective to customer segmentation for targeting. Instead of treating segmentation as a descriptive exercise, we ask: how should firms learn decision-relevant customer segments that improve targeting outcomes? This work combines machine learning, data-driven optimization, and statistical modeling to align segmentation with firms’ economic objectives.

A second stream of my research studies human–AI collaboration in the scientific process. I am interested in how AI can augment researchers’ workflows by expanding the ways researchers search, synthesize, reason, and build theory. More broadly, this stream asks how AI can be designed to enhance human creativity and rigor in knowledge production.

Together, these two streams reflect my broader research agenda: building computationally rigorous, decision-relevant, and scientifically grounded tools in the broad area of Human + AI + Decision Science.

Before joining INSEAD, I obtained my Bachelor of Engineering in Computer Science and Engineering from The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen). During my undergraduate studies, I was very lucky to receive invaluable research guidance from Baoxiang Wang and Yang Li.

I’ve also worked as a reinforcement learning researcher at Beijing Academy of Artificial Intelligence, and have interned as a ML engineer at Microsoft Research Asia, Byte Dance, and Sense Time before starting my PhD journey.