Theodoros Evgeniou - Faculty Profile | INSEAD

Theodoros Evgeniou

Decision Sciences

Theodoros Evgeniou

Professor of Decision Sciences and Technology Management

Contact

Email: [email protected]
Phone: +33 1 60 72 45 46
Campus: Fontainebleau

Research Areas

Decision Processes, Business Intelligence and Data Mining, Data Analytics in Marketing and Finance, Information Technology in Organisations

Teaching Areas

Uncertainty, Data, and Judgement, Models for Strategic Planning, Information Technology and Organisations, Data Analytics for Managers

Industry Sectors

Banking and Insurance, Information Technology, Pharmaceuticals and Health, Telecommunication Services

Biography

Theos Evgeniou is a professor of Decision Sciences and Technology Management at INSEAD and director of the INSEAD Executive Education program on Transforming your Business with AI.

He has been working on Machine Learning and AI for the past 25 years, on areas ranging from AI innovations for business process optimization and improving decisions in Marketing and Finance, to AI regulation, as well as on new Machine Learning methods. His research has appeared in leading journals, such as in Science Magazine, Nature Machine Intelligence, Machine Learning, Lancet Digital Health, Journal of Machine Learning Research, Management Science, Marketing Science, Harvard Business Review magazine, and others.

Professor Evgeniou is a member of the OECD Network of Experts on AI, an advisor for the BCG Henderson Institute, an advisor for the World Economic Forum Academic Partner for Artificial Intelligence, and together with three INSEAD alums also a co-founder of Tremau, a B2B SaaS company whose mission is to build a digital world that is safe & beneficial for all. He gives talks and consults for a number of organisations in his areas of expertise, and in the past he has been involved in developing hedge fund strategies with more than $100 million invested. He has received four degrees from MIT, two BSc degrees simultaneously, one in Computer Science and one in Mathematics, as well as a Master and a PhD degree in Computer Science.

Publications

Ramon Y., Martens D., Evgeniou T., Praet S. (2021) (Published Online). Can Metafeatures Help Improve Explanations of Prediction Models When Using Behavioral and Textual Data?. Machine Learning

Evgeniou T., Guecioueur A., Prieto R. (Forthcoming). Uncovering Sparsity and Heterogeneity in Firm-Level Return Predictability Using Machine Learning. Journal of Financial and Quantitative Analysis

Evgeniou T., Fekom M., Ovchinnikov A. S., Porcher R., Pouchol C., Vayatis N. (2023). Pandemic Lock-down, Isolation, and Exit Policies based on Machine Learning Predictions. Production and Operations Management, 32(5)

Awad E., Levine S., Anderson M., Anderson S. L., Conitzer V., Crockett M. J., Everett J. A. C., Evgeniou T., Gopnik A., Jamison J. C., Kim T. W., Liao S. M., Meyer M. N., Mikhai J., Opoku-Agyemang K., Schaich Borg J., Schroeder J., Sinnott-Armstrong W., Slavkovik M., Tenenbaum J. B. (2022). Computational Ethics. Trends in Cognitive Sciences, 26(5)

Goethals S., Martens D., Evgeniou T. (2022). The Non‑Linear Nature of the Cost of Comprehensibility. Journal of Big Data, 9

Evgeniou T., Peress J., Vermaelen T., Yue L. (2022). Network Centrality and Managerial Market Timing Ability. Journal of Financial and Quantitative Analysis, 57(2)

Candelon F., Charme di Carlo R., De Bondt M., Evgeniou T. (2021). AI Regulation Is Coming. Harvard Business Review, 99(5)

Babic B., Gerke S., Evgeniou T., Cohen I. G. (2021). Beware Explanations From AI in Health Care . Science, 373(6552)

Boza P., Evgeniou T. (2021). Artificial Intelligence to Support the Integration of Variable Renewable Energy Sources to the Power System. Applied Energy, 290

Babic B., Gerke S., Evgeniou T., Cohen I. G. (2021). Direct-to-Consumer Medical Machine Learning and Artificial Intelligence Applications. Nature Machine Intelligence, 3

Babic B., Cohen I. G., Evgeniou T., Gerke S. (2021). When Machine Learning Goes Off the Rails. Harvard Business Review, 99(1)

Ramon Y., Martens D., Provost F., Evgeniou T. (2020). A Comparison of Instance-Level Counterfactual Explanation Algorithms for Behavioral and Textual Data: SEDC, LIME-C and SHAP-C. Advances in Data Analysis and Classification, 14

Boulant O., Fekom M., Pouchol C., Evgeniou T., Ovchinnikov A. S., Porcher R., Vayatis N. (2020). SEAIR Framework Accounting for a Personalized Risk Prediction Score: Application to the COVID-19 Epidemic. Image Processing On Line, 10

Cohen I. G., Evgeniou T., Gerke S., Minssen T. (2020). The European Artificial Intelligence Strategy: Implications and Challenges for Digital Health . The Lancet Digital Health, 2(7)

Babic B., Chen D. L., Evgeniou T., Fayard A. (2020). A Better Way to Onboard AI. Harvard Business Review, 98(4)

Gerke S., Babic B., Evgeniou T., Cohen I. G. (2020). The Need for a System View to Regulate Artificial Intelligence/Machine Learning-Based Software as Medical Device. npj Digital Medicine, 3

De Cnudde S., Martens D., Evgeniou T., Provost F. (2020). A Benchmarking Study of Classification Techniques for Behavioral Data. International Journal of Data Science and Analytics, 9

Babic B., Gerke S., Evgeniou T., Cohen I. G. (2019). Algorithms on Regulatory Lockdown in Medicine. Science, 366(6470)

Kireyev P., Evgeniou T., Brandwein N. J. (2019). Preferred Networks: A Deep Learning Startup Powers the Internet of Things.

Samper-Gonzalez J., Burgos N., Bottani S., Fontanella S., Lu P., Marcoux A., Bertrand A., Bertin H., Guillon J., Wen J., Bacci M., Colliot O., Durrleman S., Habert M., Evgeniou T., Routier A. (2018). Reproducible Evaluation of Classification Methods in Alzheimer's Disease: Framework and Application to MRI and PET Data. NeuroImage, 183

Evgeniou T., Junque de Fortuny E., Nassuphis N., Vermaelen T. (2018). Volatility and the Buyback Anomaly. Journal of Corporate Finance, 49

Evgeniou T. (2017). Yet Another ADNI Machine Learning Paper? Paving The Way Towards Fully-reproducible Research on Classification of Alzheimer's Disease.

Evgeniou T., Vermaelen T. (2017). Share Buybacks and Gender Diversity. Journal of Corporate Finance, 45

Evgeniou T., Fang L., Hogarth R. M., Karelaia N. (2013). Competitive Dynamics in Forecasting: The Interaction of Skill and Uncertainty. Journal of Behavioral Decision Making, 26(4)

Lederman J., Evgeniou T. (2013). Hunt: Liquid Risks.

Toubia O., Johnson E. J., Evgeniou T., Delquie P. (2013). Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters. Management Science, 59(3)

Zhang K., Evgeniou T., Padmanabhan V. (., Richard E. (2012). Content Contributor Management and Network Effects in a UGC Environment. Marketing Science, 31(3)

Hauser J. R., Toubia O., Evgeniou T., Befurt R., Dzyabura D. (2010). Disjunctions of Conjunctions, Cognitive Simplicity, and Consideration Sets. Journal of Marketing Research, 47(3)

Evgeniou T. (2010). Catwalk: Simulation Based Re-Insurance Risk Modelling.

Abernethy J., Bach F., Evgeniou T., Vert J. (2009). Low Rank Matrix Factorization with Attributes. Journal of Machine Learning Research, 10

Pramatari K., Evgeniou T., Doukidis G. (2009). Implementation of Collaborative e-Supply Chain Initiatives: An Initial Challenging and Final Success Case from Grocery Retailing. Journal of Information Technology, 24(3)

Abernethy J., Bach F., Evgeniou T., Vert J. (2009). A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization. Journal of Machine Learning Research, 10(3)

Netzer O., Toubia O., Bradlow E., Dahan E., Evgeniou T., Feinberg F. M., Liechty J. C., Orlin J., Feit E. M., Hui K. (. S. (2008). Beyond Conjoint Analysis: Advances in Preference Measurement. Marketing Letters, 19(3-4)

Argyriou A., Evgeniou T., Pontil M. (2008). Convex Multi-Task Feature Learning. Machine Learning, 73(3)

Abernethy J., Evgeniou T., Toubia O., Vert J. (2008). Eliciting Consumer Preferences Using Robust Adaptive Choice Questionnaires. IEEE Transactions on Knowledge and Data Engineering, 20(2)

Toubia O., Evgeniou T. (2007). Optimization-Based and Machine-Learning Methods for Conjoint Analysis: Estimation and Question Design.

Evgeniou T., Pontil M., Toubia O. (2007). A Convex Optimization Approach to Modeling Consumer Heterogeneity in Conjoint Estimation. Marketing Science, 26(6)

Evgeniou T., Pramatari K., Doukidis G. (2006). Internet Enabled Collaborative Store Ordering: Veropoulos Spar Retailer (B).

Boussios K., Zacharia G., Evgeniou T. (2005). Generalized Robust Conjoint Estimation. Marketing Science, 24(3)

Evgeniou T., Cartwright P. (2005). Barriers to Information Management. European Management Journal, 23(3)

Evgeniou T., Micchelli C. A., Pontil M. (2005). Learning Multiple Tasks with Kernel Methods. Journal of Machine Learning Research, 5(4)

Pramatari K., Doukidis G., Evgeniou T. (2005). Internet Enabled Collaborative Store Ordering: Veropoulos Spar Retailer (A).

Evgeniou T., Hibon M. (2005). To Combine or Not to Combine: Selecting among Forecasts and their Combinations. International Journal of Forecasting, 21(1)

Eliseeff A., Pontil M., Evgeniou T. (2005). Stability of Randomized Learning Algorithms. Journal of Machine Learning Research, 5(1)

Cases with Extra

E.ON: Building a New AI Powered Energy World

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