About

This webpage aggregates across the capabilities of INSEAD faculty and researchers in academic publication and teaching in the areas of analytics, artificial intelligence, and big data for business and society. The work covers three levels:

  • Governance and regulation (“Responsible AI”)
  • Strategy development and implementation
  • Innovation and deployment in business process optimization and decision making

Faculty & Team

So Yeon Chun

Analytics for strategy evaluation/causal inference, Loyalty and Customer Relationship Management

Stephen E. Chick

Analytics driven business model innovation, Digital health, Optimal adaptive learning

Dragos Florin Ciocan

Revenue management, Decision-making under uncertainty, Large scale optimization

Jason Davis

AI in Big Tech, Collaboration, and Digital Strategy

Antoine Desir

Algorithms, Revenue Management, Online Marketplaces

Theodoros Evgeniou

Machine Learning Algorithms, AI Regulation and Governance, AI Adoption

Georgina Hall

Optimization, Algorithms, Statistical Inference on Networks

Dan Iancu

Optimization, Robustness, Responsible AI

Pavel Kireyev

Digital Marketplace Analytics, Machine Learning and Econometrics, Explainable AI in Marketing

Chengyi Lin

AI in health, Data strategy, Strategic impact of AI, AI ethics

Anton Ovchinnikov

Data-driven Decision Making, Responsible AI, Design and Operations of Bionic (Human and AI) Systems

Phanish Puranam

Organizational analytics, Organizations and algorithms, Org2.0

Ville Satopaa

Bayesian statistics, forecast aggregation, probabilistic forecasting

Klaus Wertenbroch

The psychology of AI: Consumer preferences for autonomy, explainability, privacy

 

Research

Working papers
Forthcoming
  • Dragos Florin Ciocan, Velibor V. Misic (Forthcoming): Interpretable optimal stopping. Management Science
  • Jue Wang, Anton Ovchinnikov: Which customers are more valuable in dynamic pricing situations? Under revision for Marketing Science
  • Klaus Wertenbroch, Rom Schrift, Joseph Alba, Alixandra Barasch, Amit Bhattacharjee, Markus Giesler, Joshua Knobe, Donald R. Lehmann, Sandra Matz, Gideon Nave, Jeffrey R. Parker, Stefano Puntoni, Yanmei Zheng, and Yonat Zwebner (Forthcoming): Autonomy in consumer choice. Marketing Letters
  • Mohammad Hossein Bateni, Yiwei Chen, Dragos Florin Ciocan, Vahab Mirrokni (Forthcoming): Fair resource allocation in a volatile marketplace. Operations Research
  • Phanish Puranam, Yash Raj Shrestha, Vivianna Fang He, Georg von Krogh (Forthcoming): Algorithm supported induction for building theory: How can we use prediction models to theorize? Organization Science
  • Stephanie Kelley, Anton Ovchinnikov: (Anti-Discrimination) laws, AI and gender bias. Under revision for Manufacturing & Services Operations Management
  • Theodoros Evgeniou, Mathilde Fekom, Anton Ovchinnikov, Raphael Porcher, Camille Pouchol, Nicolas Vayatis: Epidemic models for personalized COVID-19 isolation and exit policies using clinical risk predictions. Under review in Manufacturing & Services Operations Management
  • Vivianna Fang He, Phanish Puranam, Yash Raj Shrestha, Georg von Krogh (Forthcoming): Resolving governance disputes in communities: A study of software license decisions, Strategic Management Journal
2020
2019
2016 - 2018
Until 2015
 

Programmes

  • Executive Education Programmes
  • Courses in Degree Programmes
    • Artificial Intelligence Strategy (MBA): Pavel Kireyev
    • ART: Analytics for Retail and Travel (MBA): So Yeon Chun
    • Analytics for Responsible Management (MBA): Dan Iancu
    • Data Science (and Machine Learning) for Business (MBA): Theodoros Evgeniou, Anton Ovchinnikov, Spyros Zoumpoulis
    • Decision Models (MBA): Spyros Zoumpoulis, Miguel Lobo, Ilia Tselin, Georgina Hall
    • Digital Entrepreneurship (MBA): Jason Davis
    • Org2.0 (MBA): Phanish Puranam
    • Responsible AI (MBA): Dan Iancu
    • Social Media Analytics (MBA): Antoine Desir
    • AI Strategy for Start-ups and C-Suites (GEMBA): Phil Parker
    • Analytics for Strategy Evaluation (MIM): So Yeon Chun
    • Machine Learning and Optimization (MIM): Georgina Hall
    • Machine Learning, Causality, and Management (PhD): Pavel Kireyev
    • Foundations of Machine Learning and AI (PhD): Theodoros Evgeniou and Nicolas Vayatis
  • Educational Partnerships
 
 

Cases & Simulations

 

Knowledge & Events