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
INSEAD gratefully acknowledges the generous support of Paul Desmarais Jr. MBA’79 for Research in AI.
Faculty & Team
Research
Working papers
- So Yeon Chun, Rebecca Hamilton (2020): Should I pay with money or redeem points for this purchase? How exchange rate stability influences loyalty point redemption. Working paper
- Dan Iancu (2020): Monitoring with limited information. Working paper
- Georgina Hall, Laurent Massoulié (2020): Partial recovery in the graph alignment problem. Working paper
- Hakjin Chung, Hyun-Soo Ahn, So Yeon Chun (2020): Dynamic pricing with point redemption. Working paper
- Nicolò Bertani, Ville Satopaa, Shane Jensen (2020): Joint bottom-up method for hierarchical time-series: Application to Australian tourism. Working paper
- Phanish Puranam (2020): Human-AI collaborative decision making as an organization design problem. Working paper
- Ville Satopaa, Marat Salikhov, Philip Tetlock, Barb Mellers (2020): Bias, information, noise: The BIN model of forecasting, Working paper
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
- Andres Alban, Stephen E. Chick, Martin Forster (2020): Value-based clinical trials: selecting recruitment rates and trial lengths in different regulatory contexts. University of York (Dept. Economics and Related Studies), Discussion paper 20/1
- Anirudha Majumdar, Georgina Hall, Amir Ali Ahmadi (2020): Recent scalability improvements for semidefinite programming with applications in machine learning, control, and robotics. Annual Review of Control, Robotics, and Autonomous Systems, 3:331-360
- Boris Babic, Daniel L. Chen, Theodoros Evgeniou, Anne-Laure Fayard (2020): A better way to onboard AI. Harvard Business Review Magazine
- Boris Babic, I. Glenn Cohen, Sara Gerke, Theodoros Evgeniou (2020): The need for a system view to regulate artificial intelligence/machine learning-based software as medical device. Nature Digital Medicine, 3 (53)
- I Glenn Cohen, Theodoros Evgeniou, Sara Gerke, Timo Minssen (2020): The European artificial intelligence strategy: implications and challenges for digital health. Lancet Digital Health, 2 (7): 376-379
- Jason Davis, Vikas Aggarwal (2020): Knowledge mobilization in the face of imitation: Microfoundations of knowledge aggregation and firm‐level innovation. Strategic Management Journal, 1-32
- Pavel Kireyev (2020): Markets for ideas: prize structure, entry limits, and the design of ideation contests. The RAND Journal of Economics, 51: 563-588
- Sofie De Cnudde, David Martens, Theodoros Evgeniou, Foster Provost (2020): A benchmarking study of classification techniques for behavioral data. International Journal of Data Science and Analytics, 9: 131-173
- So Yeon Chun, Miguel A. Lejeune (2020): Risk-based loan pricing: portfolio optimization approach with marginal risk contribution. Management Science
- Theodoros Evgeniou, Ahmed Guecioueur, Rodolfo Prieto (2020): Modeling heterogeneity in firm-level return predictability with machine learning. INSEAD working paper, 2020/24/DSC
- Valeria Stourm, Scott Neslin, Eric Bradlow, Els Breugelmans, So Yeon Chun, Pedro Gardete, P. K. Kannan, Praveen Kopalle, Young-Hoon Park, David Restrepo Amariles, Raphael Thomadsen, Yuping Liu-Thompkins, Rajkumar Venkatesan (2020): Refocusing loyalty programs in the era of big data: A societal lens paradigm. Marketing Letters
2019
- Bernardo F. Quiroga, Brent Moritz, Anton Ovchinnikov (2019): Behavioral ordering, competition and profits: An experimental investigation. Production and Operations Management 28(9): 2242-2258
- Boris Babic, Sara Gerke, Theodoros Evgeniou, I.Glenn Cohen (2019): Algorithms on regulatory lockdown in medicine. Science, 366 (6470): 1202-1204
- Klaus Wertenbroch (2019): From the Editor: A manifesto for research on automation in marketing and consumer behavior. Journal of Marketing Behavior 4 (1): 1-10
- So Yeon Chun, Anton Ovchinnikov (2019): Strategic consumers, revenue management, and the design of loyalty programs. Management Science, 65 (9) 3969-3987
- So Yeon Chun, Dan A. Iancu, Nikolaos Trichakis (2019): Loyalty program liabilities and point values. Manufacturing & Service Operations Management, 22(2) 223-428
- Yanou Ramon, David Martens, Foster Provost, Theodoros Evgeniou (2019): Counterfactual Explanation Algorithms for Behavioral and Textual Data. arXiv:1912.01819
- Ziv Carmon, Rom Schrift, Klaus Wertenbroch, Haiyang Yang (2019): Designing AI systems that customers won’t hate. MIT Sloan Management Review, Reprint #61315
2016 - 2018
- Amir Ali Ahmadi, Georgina Hall (2018): DC decomposition of nonconvex polynomials with algebraic techniques. Mathematical Programming (169) 69 – 94 (Winner of the 2016 INFORMS Computing Society Best Student Paper Award)
- Andre Quentin, Ziv Carmon, Klaus Wertenbroch, Alia Crum, Douglas Frank, William Goldstein, Joel Huber, Leaf van Boven, Bernd Weber, Haiyang Yang (2018): Consumer choice and autonomy in the age of artificial intelligence and big data. Customer Needs and Solutions 5 (1-2): 28-37
- Diana Negoescu, Kostas Bimpikis, Margaret Brandeau, Dan Iancu (2018): Dynamic learning of patient response types: An application to treating chronic diseases. Management Science, 64 (8): 3469-3488
- So Yeon Chun, Michael W. Browne, Alexander Shapiro (2018): Modified distribution-free goodness-of-fit test statistic. Psychometrika 83 (1) 48 – 66
- Amir Ali Ahmadi, Georgina Hall, Ameesh Makadia, Vikas Sindhwani (2017): Geometry of 3D environments and sum of squares polynomials. Computer Vision (Conference paper for RSS 2017)
- Edward I. George, Veronika Rockova, Paul R Rosenbaum, Ville A Satopaa, Jeffrey H Silber (2017): Mortality rate estimation and standardization for public reporting: Medicare’s hospital compare, Journal of the American Statistical Association, 112:519: 933-947
- Eric C. Ni, Dragos Florin Ciocan, Shane G. Henderson, Susan R. Hunter (2017): Efficient ranking and selection in parallel computing environments. Operations Research, 65 (3)
- Stephen Chick, Martin Forster, Paolo Pertile (2017): A Bayesian decision theoretic model of sequential experimentation with delayed response. Journal Royal Statistical Society Series B, 79 (5): 1439-1462
- Ville Satopaa, Shane T. Jensen, Robin Pemantle, Lyle H. Ungar (2017): Partial information framework: Model-based aggregation of estimates from diverse information sources, The Electronic Journal of Statistics, 11: 3781-3814.
- Emmanuel Abbe, Afonso S. Bandeira, Georgina Hall (2016): Exact recovery in the stochastic block model. IEEE transactions on information theory, 62 (1) 471 – 487 (Winner of the 2020 Information Theory Best Paper Award)
- Jing Xie, Peter I. Frazier, Stephen E. Chick (2016): Bayesian optimization via simulation with pairwise sampling and correlated prior beliefs. Operations Research 64 (2): 542-559
- So Yeon Chun, Anton J. Kleywegt, Alexander Shapiro (2016): When friends become competitors: The design of resource exchange alliances. Management Science, 63 (7) 2127-2145
- Ville Satopaa, Robin Pemantle, Lyle H. Ungar (2016): Modeling probability forecasts via information diversity, Journal of the American Statistical Association, 111.516: 1623-1633
Until 2015
- Dan Iancu, Nikolaos Trichakis (2014): Pareto efficiency in robust optimization. Management Science, 60 (1): 130-147
- Dan Iancu, Nikolaos Trichakis (2014): Fairness and efficiency in multiportfolio optimization. Operations Research, 62 (6): 1285-1301
- Ville Satopaa, Shane T. Jensen, Barbara A. Mellers, Philip E. Tetlock, Lyle H. Ungar (2014): Probability aggregation in time-series: Dynamic hierarchical modeling of sparse expert beliefs, Annals of Applied Statistics, 8.2: 1256-1280
- Dan Iancu, Mayank Sharma, Maxim Sviridenko (2013): Supermodularity and affine policies in dynamic robust optimization. Operations Research 61 (4): 941-956
- Dimitris Bertsimas, Dan Iancu, Dmitriy Katz (2013): A new local search algorithm for binary optimization. INFORMS Journal on Computing, 25 (2): 208-221
- Dragos Florin Ciocan, Vivek Farias (2012): Model predictive control for dynamic resource allocation. Mathematics of Operations Research, 37 (3)
- So Yeon Chun, Alexander Shapiro, Stan Uryasev (2012): Conditional value-at-risk and average value-at-risk: Estimation and asymptotics. Operations Research, 60 (4) 739-756
- Stephen E. Chick, Peter Frazier (2012): Sequential sampling with economics of selection procedures. Management Science 58 (3): 550-569
- Dimitris Bertsimas, Dan Iancu, Pablo Parrilo (2011): A Hierarchy of Near-Optimal Policies for Multistage Adaptive Optimization. IEEE Transactions on Automatic Control, 56 (12): 2809-2824
- John R. Hauser, Olivier Toubia, Theodoros Evgeniou, Rene Befurt, Daria Dzyabura (2010): Disjunctions of conjunctions, cognitive simplicity, and consideration sets. Journal of Marketing Research, 47 (3): 485-496
- So Yeon Chun, Alexander Shapiro (2010): Construction of covariance matrices with a specified discrepancy function minimizer, with application to factor analysis. SIAM Journal on Matrix Analysis and Applications, 31(4) 1570–1583
- Jacob Abernethy, Francis Bach, Theodoros Evgeniou, Jean-Philippe Vert (2009): A new approach to collaborative filtering: Operator estimation with spectral regularization. Journal of Machine Learning Research, 10 (29): 803-826
- So Yeon Chun, Alexander Shapiro (2009): Normal versus noncentral chi-square asymptotics of misspecified models. Multivariate Behavioral Research, 44(6) 803-827
- Andreas Argyriou, Theodoros Evgeniou, Massimiliano Pontil (2008): Convex multi-task feature learning. Machine Learning, 73(3): 243-272
- Theodoros Evgeniou, Massimiliano Pontil, Olivier Toubia (2007): A convex optimization approach to modeling consumer heterogeneity in conjoint estimation. Marketing Science, 26 (6): 805-818
- Constantine Papageorgiou, Theodoros Evgeniou, Tomaso A. Poggio (2000): A trainable pedestrian detection system. Proceedings of Intelligent Vehicles.
- Theodoros Evgeniou, Massimiliano Pontil, Tomaso Poggio (2000): Regularization networks and support vector machines. Advances in Computational Mathematics, 13 (1): 1-50
Programmes
- Executive Education Programmes
- AI for Business (OEP): Programme Directors: Phanish Puranam & Theodoros Evgeniou. Faculty: Sameer Hasija, Philip M. Parker, Ville Satopaa
- Leading Digital Transformation and Innovation (OEP): Programme Directors: Nathan Furr & Jason Davis. Faculty: Charles Galunic
- Strategy in the Age of Digital Disruption (Online OEP): Peter Zemsky
- Transforming Your Business with AI (Online OEP): Phanish Puranam, Theodoros Evgeniou
- The Future of AI: Seizing the Opportunity (with Singularity University): Peter Zemsky
- AI Strategy for the Chief Marketing Officer (CSP): Pavel Kireyev
- Human Judgment vs. AI: Identifying Opportunities (CSP): Miguel Lobo
- Strategic Impact of AI (CSP): Chengyi Lin
- 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
- Theodoros Evgeniou, Pal Boza (2020): E.ON: Building a new AI powered energy world, INSEAD case
- Peter Zemsky, Pavel Kireyev, Lisa Duke (2020): ObEN PAI: Building a world of personal AI avatars, INSEAD case
- Jason Davis, Minh Vo, Anne Yang (2020): Circles.Life: Business model innovation and digital entrepreneurship in telecommunications, INSEAD case
- Jason Davis, Anne Yang (2020): Cloud wars go global: How Amazon, Microsoft, Google and Alibaba compete in web services, INSEAD case
- Phanish Puranam (2020): AI for customer experience: Intelligent automation in the insurance adjustment claims process (A) & (B), INSEAD case
- Pavel Kireyev, Theos Evgeniou, Nancy J. Brandwein (2019): Preferred networks: A Deep learning startup powers the internet of things, INSEAD case
- Jason Davis, Minh Vo, Anne Yang (2019): ByteDance beyond China: Leveraging consumer Artificial Intelligence (AI) from Toutiao to Musical.ly and TikTok, INSEAD case
- Anton Ovchinnikov (2018): Private banking advisers at BCB Edmonton (A), Darden School of Business Case QA-0905
- Anton Ovchinnikov (2017): Retention modeling at scholastic travel company (A), Darden School of Business Case QA-0864
- Ridhima Aggarwal, Stephen E. Chick, Francoise Simon (2016): PatientsLikeMe: Using social network health data to improve patient care. INSEAD Case
- Kyle Jacques Rose, Stephen E. Chick (2016): Mobile health in diabetes: mySugr’s monster approach. INSEAD Case
- Anton Ovchinnikov, Alexander Pyshkov (2016): Outsourcing, near-sourcing, and supply chain flexibility in the apparel industry (A), Darden School of Business Case QA-0854
- Ridhima Aggarwal, Stephen E. Chick (2013): Laastari: Building a retail health clinic chain. INSEAD Case
- Albert Angehrn (2020): The “Boost AI” Simulation – The Artificial Intelligence Diffusion Challenge
Knowledge & Events
- Pavel Kireyev, Manoj Saxena, Joanna Gordon (2020): Is AI the silver bullet against COVID 19? INSEAD Conversations, Tech Talk X
- Theodoros Evgeniou, David R. Hardoon, Anton Ovchinnikov (2020): Balancing data policies: What COVID-19 taught us, The Global Centre for Technology, Innovation and Sustainable Development
- Pál Boza, Theodoros Evgeniou (2020): How data is transforming the energy sector, INSEAD Knowledge
- Theodoros Evgeniou, Xian-Sheng Hua, Guénaël Rodier (2020): Harnessing technology in our battle with COVID-19, INSEAD Knowledge
- Phanish Puranam (2020): Where AI can help your business (and where it can’t), INSEAD Knowledge
- Ziv Carmon, Rom Schrift, Klaus Wertenbroch, Haiyang Yang (2020): Consumer autonomy violations and the coming AI backlash, INSEAD Knowledge
- Chengyi Lin, Jean-Michel Moslonka, Bertille Le Bihan, Anaïs Masetti (2020): White paper: Accelerating AI adoption in bio-pharma through collaboration. INSEAD, Agalio, Early Metrics
- Chengyi Lin, Genia Kostka (2020): Social credits and security: embracing the world of ratings. Kaspersky daily
- Jason Davis, Vikas Aggarwal (2020): How Spotify and TikTok beat their copycats, HBR digital
- Theodoros Evgeniou, David R. Hardoon, Anton Ovchinnikov (2020): What happens when AI is used to set grades? HBR digital
- Theodoros Evgeniou, David R. Hardoon, Anton Ovchinnikov (2020): Leveraging AI to battle this pandemic – and the next one, HBR digital
- Theodoros Evgeniou: Tech meets COVID-19: Lessons from around the world, INSEAD Conversations, 17.4.2020
- Theodoros Evgeniou: AI Regulatory Challenges, 1st meeting of the OECD parliamentary group on Artificial Intelligence, 26.2.2020
- Theodoros Evgeniou: Balancing AI productivity and responsibility, Sustainable Development Goals Tent in Davos, 23.1.2020
- Anton Ovchinnikov (2019): Managerial biases cost your firm more than you think, INSEAD Knowledge
- Jason Davis (2019): Three objectives for moving forward with AI, INSEAD Knowledge
- Jason Davis (2019): The TikTok strategy: using AI platforms to take over the world, INSEAD Knowledge
- Pavel Kireyev (2019): A start-up’s evolution from AI lab to AI business, INSEAD Knowledge
- Pavel Kireyev (2019): Meet the algorithms planning your next online purchase, INSEAD Knowledge
- So Yeon Chun, Anton Ovchinnikov (2019): The optimal design of loyalty programmes, INSEAD Knowledge
- Ville Satopaa (2019): Want better forecasting? Silence the noise, Podcast Interview with Knowledge@Wharton
- Ville Satopaa (2019): The secret ingredients of ‘Superforecasting’, INSEAD Knowledge
- Theodoros Evgeniou (2019): Preparing your firm for AI, INSEAD Knowledge
- Theodoros Evgeniou (2019): AI = Artificial imagination? INSEAD Knowledge
- Theodoros Evgeniou (2019): The pivotal management challenge of the AI era, INSEAD Knowledge
- Phanish Puranam, Prothit Sen (2019): Enlightened by randomness, INSEAD Knowledge
- Phanish Puranam (2018): (Re)-Designing organisations in the Age of Algorithms, INSEAD Knowledge
- Ville Satopaa (2017): Warning: Do not just average predictions, INSEAD Knowledge
- Ville Satopaa (2017): Improving the accuracy of hospital rankings, INSEAD Knowledge
- American Statistical Association (2017): New analysis finds Medicare program underestimates heart attack mortality rates
- Ville Satopaa (2017): After the surprise of 2016, here’s how pollsters can do better in predicting election results, Washington Post
- Matt Palmquist (2015): Why loyalty programs based on consumer spending can be a win-win, Strategy+Business, PwC Strategy& LLC
- Edmund Andrews (2015): Dan Iancu: Tapping a moral philosopher to solve a money manager’s dilemma, Insights by Stanford Business
- Pavel Kireyev (2020): AI Strategy Special Lecture, INSEAD x HBS Alumni Event, Roppongi Academy Hills, Tokyo
- Pavel Kireyev (2019): Data-Driven Pricing and Advertising, GITEX, Dubai
- Pavel Kireyev (2019): AI in Creative Industries, AI Everything, Dubai
- Chengyi Lin (2019): AI start-up bootcamp, AI Everything, Dubai
- Pavel Kireyev (2019): WeWork Paris and Harvard Alumni Entrepreneurs Panel on AI, Paris
- Klaus Wertenbroch (2019): Marketing Dystopia? INSEAD AI Forum Singapore
- Klaus Wertenbroch (2018): Protecting Consumer Sovereignty in the Age of Big Data and AI, Keynote Presentation, Annual Behavioural Economics Symposium, Civil Service College, Singapore
- Theodoros Evgeniou, Pavel Kireyev (2018): INSEAD x AI, INSEAD AI Forum Station F, Paris