Publications

Works ahead!

This page is still in progress



  1. A.Fernandes-Machado, A.Charpentier, E.Flachaire, E.Gallic & F.Hu, From Uncertainty to Precision: Enhancing Binary Classifier Performance through Calibration, 2024. ArXiv:2402.07790.

  2. A.Fernandes Machado, F.Hu, P.Ratz, E.Gallic, A.Charpentier, Geospatial Disparities: A Case Study on Real Estate Prices in Paris, 2024. ArXiv:2401.16197

  3. O.Côté, M.P.Côté, A. Charpentier, A Fair price to pay: exploiting causal graphs for fairness in insurance, 2024. SSRN:4709243

  4. F. Hu, P. Ratz A. Charpentier, Parametric Fairness with Statistical Guarantees, 2023. doi:10.48550/arXiv.2310.20508

  5. F. Hu, P. Ratz A. Charpentier, Addressing Fairness and Explainability in Image Classification Using Optimal Transport, 2023. doi:10.48550/arXiv.2306.12912

  6. X.Vamparys A. Charpentier, Intelligence artificielle et individualisation des garanties en assurance: échec ou retard à l’allumage ?, 2023.

  7. S.Stocksieker, A.Charpentier, D.Pommeret. Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory. arXiv:2308.02966, 2023. doi:10.48550/arXiv.2308.02966

  8. F. Foutel-Rodier, A. Charpentier, H. Guérin Optimal vaccination policy to prevent endemicity: a stochastic model. arXiv:2306.13633, 2022. doi:10.48550/arXiv.2306.13633

  9. A. Charpentier Quantifying fairness and discrimination in predictive models . arXiv:2212.09868, 2022. doi:10.48550/arXiv.2212.09868

  10. H. Hu , A. Charpentier, M. Ghossoub, A. Schied Multiarmed Bandits Problem Under the Mean-Variance Setting . arXiv:2212.09192, 2022. doi:10.48550/arXiv.2212.09192

  11. M. Hassan, N. Sakr, A. Charpentier Government Intervention in Catastrophe Insurance Markets: A Reinforcement Learning Approach . arXiv:2207.01010, 2022. doi:10.48550/arXiv.2207.01010

  12. L. Barry, A. Charpentier L'équité de l'apprentissage machine en assurance hal-03561709, 2022. doi:

  13. L. Barry, A. Charpentier The Fairness of Machine Learning in Insurance: New Rags for an Old Man? . hal-03561709, 2022. doi:

  14. V. Grari, A. Charpentier, V. Lamprier, M. Detyniecki A fair pricing model via adversarial learning . ArXiv: 2202.12008, 2022. doi:10.48550/arXiv.2202.12008

  15. A. Charpentier, L. Kouakou, M. Löwe, P. Ratz , F. Vermet Collaborative Insurance Sustainability and Network Structure. ArXiv: 2107.02764, 2021, doi:10.48550/arXiv.2107.02764.

  16. O. Cabrignac, A. Charpentier, E. Gallic Modeling Joint Lives within Families. arxiv-2006.08446 2020, doi:10.48550/arXiv.2006.08446.

  17. A. Charpentier, A. Galichon, L. Vernet Optimal transport on large networks a practitioner guide. arXiv:1907.02320 2019, doi:10.48550/arXiv.1907.02320.

  18. E. Belz , A. Charpentier Données Agrégées et Variables Compositionnelles : Note Méthodologique. hal:2097031 2019.

  19. A. Charpentier, E. Flachaire Extended Scale-Free Networks. arxiv-1905.10267 2019, doi:10.48550/arXiv.1905.10267.

  20. D. Cocteau-Senn, A. Charpentier & R. Bigot La protection des données personnelles en assurance : dialogue du juriste avec l'actuaire hal 2018.

  21. A.D. Barry , A. Charpentier & K. Oualkacha Quantile and Expectile Regression for random effects model hal-01421752 2016.

  22. M.Boudreault, A.Charpentier Multivariate integer-valued autoregressive models applied to earthquake counts. arXiv:1112.0929 2011.

  23. A.Charpentier Pricing catastrophe options in incomplete markets citeseerx:10.1.1.572.4606 2008.

  24. A.Charpentier Reinsurance, ruin and solvency issues: some pitfalls. hal-00463381 2010.

  25. A.Charpentier, D.Causeur Large-scale significance testing of the full Moon effect on deliveries Large-scale significance testing of the full Moon effect on deliveries 2009.



  1. L. Barry, A. Charpentier Melting contestation: insurance fairness and machine learning. Ethics and Information Technology, 2023. doi:10.1007/s10676-023-09720-y

  2. A. Barry , K. Oualkacha, A. Charpentier Alternative fixed-effects panel model using weighted asymmetric least squares regression . Statistical Methods & Applications, 2023. doi:10.1007/s10260-023-00692-3

  3. L. Barry, A. Charpentier L'équité de l'apprentissage machine en assurance Statistique et Société, 2023.

  4. A. Charpentier, M. James, H. Ali Predicting Drought and Subsidence Risks in France . Natural Hazards and Earth System Sciences., 2022. doi:10.5194/nhess-2021-214

  5. A. Charpentier, Flachaire E. Pareto models for top incomes and wealth. Journal of Economic Inequality, 2021. doi:10.1007/s10888-021-09514-6

  6. A. Cayol, R. Bigot, A. Charpentier, Risque de pandémie, pertes d’exploitation et incertitudes des garanties assurantielles. Responsabilité civile et assurance, 2022.

  7. A. Charpentier, Denuit, M., Trufin, J. Autocalibration and Tweedie-dominance for Insurance Pricing with Machine Learning. Insurance: Mathematics & Economics, 2021. doi:10.1016/j.insmatheco.2021.09.001

  8. A. Barry, K. Oualkacha, A. Charpentier A new GEE method to account for heteroscedasticity, using asymmetric least-square regressions. Journal of Applied Statistics 2021. doi:10.1080/02664763.2021.1957789

  9. A. Charpentier, S. Mussard, T. Ouraga Principal Component Analysis: A Generalized Gini Approach. European Journal of Operational Research 2021.doi:10.1016/j.ejor.2021.02.010

  10. A. Charpentier, R. Élie, C. Remlinger Reinforcement Learning in Economics and Finance. Computational Economics, 2021.doi:10.1007/s10614-021-10119-4

  11. A. Charpentier, L. Barry, M. James Insurance against Natural Catastrophes: Balancing Actuarial Fairness and Social Solidarity. Geneva Paper on Risk and Insurance, 2021.doi:10.1057/s41288-021-00233-7
    hal doi

  12. A. Charpentier, R. Élie, M. Laurière, V.C. Tran COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability. Mathematical Modelelling of Natural Phenomena 2020.doi:10.1051/mmnp/2020045

  13. L. Barry & A. Charpentier Personalization as a Promise: Can Big Data Change the Practice of Insurance?. Big Data & Society, 2020. doi:10.1177/2053951720935143

  14. A. Charpentier & E. Gallic . Can historical demography benefit from the collaborative data of genealogy websites?. Population 2020 doi:10.3917/popu.2002.0391

  15. A. Charpentier & E. Gallic. Using collaborative genealogy data to study migration: a research note. The History of the Family 2019, doi:10.1080/1081602X.2019.1641130

  16. A. Charpentier, N., Ka, S. Mussard & O.H. Ndiaye Gini Regressions and Heteroskedasticity. Econometrics, 7, 2019, doi:10.3390/econometrics7010004

  17. A. Charpentier, E. Flachaire & A. Ly Econometrics and Machine Learning. Economics & Statistics 2018, doi:10.24187/ecostat.2018.505d.1970

  18. A. Charpentier & B. Coulmont We are not alone ! (at least, most of us). Homonymy in large scale social groups. Significance 2018, doi:10.1111/j.1740-9713.2018.01108.x

  19. A. Charpentier, A. David & R. Elie Optimal Claiming Strategies in Bonus Malus Systems and Implied Markov Chains . Risks, 2017.

  20. A. Charpentier & M. Pigeon Macro vs. Micro Methods in Non-Life Claims Reserving (an Econometric Perspective) . Risks,, 4: 1-18, 2016.

  21. G.Geenens, A.Charpentier, D.Paindaveine Probit transformation for nonparametric kernel estimation of the copula density. Bernoulli, 23: 1848-1873, 2017.

  22. A.Charpentier, A.Galichon, M.Henry Local Utility and Multivariate Risk Aversion Mathematics of Operations Research , 41: 466-476 , 2016.

  23. A.Charpentier, E.Gallic Kernel density estimation based on Ripley’s correction. Geoinformatica, 20: 95-116, 2016.

  24. A.Charpentier, E.Flachaire Log-transform kernel density estimation of income distribution. Actualité Economique, 91 :141-149, 2015.

  25. C. Tavéra, J.-C. Poutineau, J.-S. Pentecôte, I. Cadoret-David, A. Charpentier, C. Guéguen, M. Huchet-Bourdon, J. Licheron & G. L'Oeillet The "Mother of All Puzzles" at thirty: a meta-analysis. International Economics, 141 :80-96, 2015.

  26. M.T.Bastos, A.Charpentier, D.Mercea Tents, Tweets, and Events: The Interplay Between Ongoing Protests and Social Media. Journal of Communication, 65: 320–350, 2015.

  27. A.Charpentier, B.Le Maux Natural catastrophe insurance: How should the government intervene?. Journal of Public Economics, 115: 1-17, 2014.

  28. A.Charpentier, M.Durand Modeling earthquake dynamics. Journal of Seismology, 19: 721-739, 2015.

  29. A.Charpentier, A.-L.Fougères, C.Genest and J.G.Nešlehová Multivariate Archimax copula. Journal of Multivariate Analysis, 126 :118-136, 2014.

  30. A.Charpentier, S.Mussard Income Inequality Games Journal of Economic Inequality, 9: 529–554, 2011.

  31. A.Charpentier On the return period of the 2003 heat wave. Climatic Change, 109: 245–260, 2011.

  32. A.Charpentier, A.Oulidi Beta kernel quantile estimators of heavy-tailed loss distributions. Statistics and Computing, 20: 35–55, 2010.

  33. A.Charpentier, A.Oulidi Estimating allocations for value-at-risk portfolio optimization. Mathematical Methods of Operations Research, 69: 395, 2009.

  34. A.Charpentier, J.Segers Tails of multivariate Archimedean copulas. Journal of Multivariate Analysis, 100: 1521–1537, 2009.

  35. A. Charpentier, D. Sibaï Dynamic flood modeling: combining Hurst and Gumbel's approach. Environmetrics, 20: 32–52, 2009.

  36. A.Charpentier Insurability of climate risks.. The Geneva Papers on Risk and Insurance, 33: 91–109, 2008.

  37. A.Charpentier Dynamic dependence ordering for Archimedean copulas and distorted copulas. Kybernetika, 44: 777-794, 2008.

  38. A.Charpentier, J.Segers Convergence of Archimedean copulas. Statistics and Probability Letters, 78: 412-419, 2008.

  39. A.Charpentier, J.Segers Lower tail dependence for Archimedean copulas: Characterizations and pitfalls. Insurance: Mathematics and Economics, 40: 525-532, 2007.

  40. A.Charpentier, A.Juri Limiting dependence structures for tail events, with applications to credit derivatives. Journal of Applied Probability, 43: 563-586, 2006.

  41. Boüette, J.-C., Chassagneux, J.-F., Sibaï, D., Terron., R. & Charpentier, A Wind in Ireland: long memory or seasonal effect?. Stochastic Environmental Research and Risk Assessment, 20: 141, 2006.



  1. S.Stocksieker , A. Charpentier, D.Pommeret. Boarding for ISS: Imbalanced Self-Supervised Discovery of a Scaled Autoencoder for Mixed Tabular Datasets. IEEE World Congress on Computational Intelligence - IEEE WCCI, 2024. doi:10.48550/arXiv.2403.15790

  2. F. Hu, P. Ratz A. Charpentier, A Sequentially Fair Mechanism for Multiple Sensitive Attributes, AAAI-2024, 38th Annual AAAI Conference on Artificial Intelligence, 2024, doi:10.48550/arXiv.2309.06627

  3. A. Charpentier, F. Hu, P. Ratz Mitigating Discrimination in Insurance with Wasserstein Barycenters. BIAS 2023, 3rd Workshop on Bias and Fairness in AI, International Workshop of ECML PKDD, 2023. doi:10.48550/arXiv.2306.12912

  4. S.Stocksieker , A. Charpentier, D.Pommeret. Data Augmentation for Imbalanced Regression. Proceedings of The 26th International Conference on Artificial Intelligence and Statistics - AISTATS, 2023. doi:10.48550/arXiv.2302.09288/

  5. F. Hu, P. Ratz , A. Charpentier, Fairness in Multi-Task Learning via Wasserstein Barycenters . Machine Learning and Knowledge Discovery in Databases: Research Track (ECML PKDD 2023), 2023. doi:10.1007/978-3-031-43415-0_18 and doi:10.48550/arXiv.2306.12912


Books



  1. A.Charpentier, Insurance, Biases, Discrimination and Fairness. Springer 2024

  2. G.Bénéplanc, A.Charpentier, P.Thourot Manuel d'Assurance. Presses Universitaires de France. 2022

  3. A.Charpentier Computational Actuarial Science with R. CRC Press. 2014.

  4. A. Charpentier & C. Dutang Actuariat avec R. CRAN. 2013.

  5. M.Denuit, A.Charpentier Mathématiques de l’assurance non-vie - Tarification et provisionnement (Tome 2). Economica. 2005.

  6. M.Denuit, A.Charpentier Mathématiques de l’assurance non-vie - Principes fondamentaux de théorie du risque (Tome 1). Economica. 2004.

  7. Collective Actuarial Community Loss Data Analytics. An open text authored by the Actuarial Community. 2019.

Reports

  1. A.Charpentier Assurance : Discrimination, biais et équité. Institut Louis Bachelier, Opinions & Débats, 25, 2022

  2. A.Charpentier Insurance : Discrimination, biaises and fairness. Institut Louis Bachelier, Opinions & Débats, 25, 2022

Chapters



  1. A. Charpentier Quantifying Fairness and Discrimination in Predictive Models. in Machine Learning for Econometrics and Related Topics, Vladik Kreinovich, Songsak Sriboonchitta, Woraphon Yamaka Eds. Springer Nature doi:10.1007/978-3-031-43601-7_3

  2. A. Charpentier, E. Flachaire, E. Gallic Optimal Transport for Counterfactual Estimation: A Method for Causal Inference . in Optimal Transport Statistics for Economics and Related Topics, Ngoc Thach, Kreinovich, Thanh Ha & Duc Trung Eds. Springer Nature doi:10.1007/978-3-031-35763-3_3

  3. A.Charpentier, E.Flachaire Pareto Models for Risk Management. in Recent Econometric Techniques for Macroeconomic and Financial Data, G. Dufrénot & T. Matsuki Ed., 2020.

  4. A.Charpentier, M.Denuit On limits for machine learning algorithms in insurance. in Insurance data analytics, F.Planchet & C.Y.Robert Ed., 2020.

  5. A.Charpentier Central Limit Theorem. in The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation, B. Frey Ed., 2018.

  6. A.Charpentier Prévision avec des copules en finance. in Prévisions en Finance, Charles, Darne & Ferrara Eds., 2017.

  7. A.Charpentier, R.Kaas Introduction. in Computational Actuarial Science With R, Charpentier, A. Eds., 2014.

  8. A.Charpentier, S.Tufféry Statistical Learning. in Computational Actuarial Science With R, Charpentier, A. Eds., 2014.

  9. B.Escoto, A.Charpentier Bayesian Philosophy. in Computational Actuarial Science With R, Charpentier, A. Eds., 2014.

  10. A.Charpentier Modèles statistiques du risque en assurance. in Statistique du Risque, Droesbeke, Maumy-Bertrand, Saporta & Thomas-Agnan Eds., 2014.

  11. A.Charpentier Copules et Risques Multiples. in Statistique du Risque, Droesbeke, Maumy-Bertrand, Saporta & Thomas-Agnan Eds., 2014.

  12. A.Charpentier Mesures de Risques. in Statistique du Risque, Droesbeke, Maumy-Bertrand, Saporta & Thomas-Agnan Eds., 2014.

  13. A.Charpentier, J.D.Fermanian, O.Scaillet The estimation of copulas: Theory and practice. in Copula Methods in Derivatives and Risk Management: From Credit Risk to Market Risk, Rank Eds., 2006.


    Code

    CASDataset (R)

      
        install.packages("CASdatasets", 
    	repos = "http://cas.uqam.ca/pub/", type="source")
      
    

    Equipy (python)

      
        pip install --upgrade git+https://github.com/equilibration/equipy.git
      
    

    Review

    1. A.Charpentier La bataille de la Sécu: Une histoire du système de santé. Risques, 125, .

    2. L.Barry, A.Charpentier Rapport Langreney : lutter contre le désengagement des assureurs dans la couverture des risques climatiques . Dalloz Actualité.

    3. A.Charpentier La bataille de la Sécu: Une histoire du système de santé. Risques, 125, .

    4. A.Charpentier Homo Deus: le salut par l'algorithme ?. Risques, 110, .

    5. A.Charpentier Weapons of Math Destruction. How Big Data Increases Inequality and Threatens Democracy. Risques, 108, .

PhD Committees

HDR Jury
Christophe Dutang 2021
Some statistical and game-theoretic models with an actuarial perspective
Université Paris Daupine
Nabil Kazi-Tani 2021
Contrôle stochastique, mesures de risque et théorie de la ruine : quelques problèmes de gestion des risques
Université de Lyon 1

PhD Jury
Marouane Il-Idrissi 2024
Développement de méthodes d'interprétabilité en apprentissage automatique pour la certification des intelligences artificielles reliées aux systèmes critiques
Université de Toulouse, France
Francis Duval 2024
Université du Québec à Montréal, Canada
Geoffrey Ecoto 2023
Modélisation et apprentissage machine learning appliqués à l’estimation des dommages consécutifs à la survenance d’un événement de sécheresse par retrait-gonflement des argiles dans le cadre du régime d’indemnisation des catastrophes naturelles français
Université Paris Cité, France
Eric Vansteenberghe 2023
Three essays in banking and insurance
École des Hautes Études en Sciences Sociales, France
Dafnis Krasniqi 2023
Quelques nouveaux modèles d'apprentissage statistique pour données de comptage et application en assurance
Université Paris-Sorbonne, France
Bertille Picard 2023
Counterfactuals in economics: the challenges of personalized estimation using machine learning
Aix-Marseille School of Economics, France
Lucas de Lara 2023
Counterfactual Models for Fair and Explainable Machine Learning: A Mass Transportation Approach
Université de Toulouse, France
Mohamed Ouhourane 2023
La régression asymétrique quantile et expectile en grande dimension et la sélection de variables par groupes
UQAM, Montréal, Canada
Pierre Chatelain 2023
Tarification à l’adresse en assurance habitation individuelle
Université de Lyon, France
Guillaume Boglioni Beaulieu 2022
Pairwise versus mutual independence: visualisation, actuarial applications and central limit theorems
UNSW, Australia
Meryem Yankol Schalck 2022
Investigating New Machine Learning Approaches for Financial Fraud Detection and Survival Analysis in Insurance Industries
Université d’Orléans, France
Antoine Heranval 2022
Application de méthodes d’apprentissage statistique pour l’évaluation de la nature et du coût des dommages assurés liés aux événements naturels en France
Sorbonne Université, France
Vincent Grari 2022
Adversarial mitigation to reduce unwanted biases in machine learning
Sorbonne Université, France
François Hu 2022
Semi-supervised learning in insurance: fairness and active learning
Institut Polytechnique de Paris, France
Ihsan Chaoubi 2022
Modélisation de la dépendance et apprentissage automatique
Université Laval, Québec, Canada
Enora Belz 2021
Econométrie des données imparfaites : méthodes et applications
Université de Rennes 1
Arthur Maillart 2021
Quelques méthodes d’explicabilité pour les modèles d’apprentissage statistique en actuariat.
Université de Lyon 1
Debora Zaparova 2021
Information et assurance : la segmentation des risques et la prévention dans un contexte de disponibilité des données
Université de Strasbourg
Loann Desboulets 2020
Variable selection on non-linear manifolds
Aix-Marseille School of Economics
Lenin Arango Castillo 2020
Long-Range Dependence in Stationary Gaussian Time Series: An Application to Stock Trading Volume and Realized Volatility
Queen's University
Sander Devriendt 2020
Sparse predictive modeling with applications in insurance pricing and mortality forecasting
KU Leuven
Pierrick Piette 2019
Contributions de l’Apprentissage Statistique à l’Actuariat et la Gestion des Risques Financiers
Université de Lyon 1
Oscar Alberto Quijano Xacur 2019
Computational Bayesian Methods for Insurance Premium Estimation
Concordia University, Montréal
Yang Jiao 2018
Applications of Artificial Intelligence in E-Commerce and Finance
Telecom SudParis
Edouard Debonneuil, 2018
Analyses prospectives de mortalité : approches actuarielle et biomédicale
Université de Lyon 1, France
Alexandre Godzinski, 2017
Three empirical essays on moral hazard identification in insurance
École des Hautes Études en Sciences Sociales, PSE
Fattouma Souissi, 2016
Gini-PLS regression: an application on European agriculture incomes inequalities
Université de Montpellier
Arnaud Goussebaïle, 2015
Prevention and Insurance of Natural Catastrophes
Ecole Polytechnique
Leo Guelman, 2015
Optimal personalized treatment learning models with insurance applications
Universitat de Barcelona
Przemyslaw Sloma, 2014
Contribution to the weak convergence of empirical copula processes & to the stochastic claims reserving in general insurance
Université Paris VI
Mathieu Pigeon, 2014
Multivariate Skew Models with Applications in Loss Reserving and Reinsurance
Université Catholique de Louvain
Julien Tomas, 2013
Quantifying biometric life insurance risks with nonparametric smoothing methods
Universiteit van Amsterdam
Aymric Kamega, 2011
Outils théoriques et opérationnels adaptés au contexte de l'assurance vie en Afrique subsaharienne francophone: Analyse et mesure des risques liés à la mortalité
Université Lyon I
Tarek Zari, 2010
Contribution à l'étude du processus empirique de copule
Université Paris VI
Meriem Maatig, 2010
Effets des comportements risqués des conducteurs sur la sinistralité: Analyse empirique sur des données françaises
Université Paris II Assas
Noureddine Ben Lagha, 2008
Nouvelles approches de l'étude de la sinistralité en assurance automobile
Université Paris II Assas
PhD invitation
Charles Condevaux (Univ. Nîmes, France) Gilles Hacheme (AMSE, France) Loann Desboulets (AMSE, France) Bertille Picard (AMSE, France) Samira Ait Mekideche (University of Béjaïa, Algeria, جامعة بجاية) Fallou Niakh (ENSAE, CREST, Institut Polytechnique, France)

Follow-up PhD committee
Arthur Maillart Debora Zaparova Samuel Piveteau Bertille Picard Xavier Vamparys

MSc Committees

Francis Duval Roxane Turcotte Olivier Binette Julie Bélanger Alexandre Roy-Gaumond Paul Mathivon

Reviewer

Journals (reviews)
Stochastic Environmental Research and Risk Assessment Theory and Decision Insurance: Mathematics and Economics Journal of Banking and Finance The Canadian Journal of Statistics Journal of Computational and Graphical Statistics Journal of Multivariate Analysis Communications in Statistics: Theory and Methods Quantitative Finance Journal of the American Statistical Association TEST Asia-Pacific Journal of Financial Studies Statistics and Decision Kybernetika European Journal of Finance Mathematics and Financial Economics Statistica Sinica Extremes Physics and Chemistry of the Earth Computational Statistics Geneva Papers on Risk and Insurance Bernoulli Water Ressources Statistics & Probability Letters Mathematical Finance Journal of Risk Journal of Hydrology Scandinavian Actuarial Journal Advances in Statistical Analysis European Actuarial Journal Metrika Journal of Statistical Planning and Inference Annals of Applied Statistics Constructive Approximation Econometric Reviews Annals of Economics and Statistics Annals of Actuarial Science Journal of the Royal Statistical Society – Series B Mathematics of Social Sciences Economic Theory ASTIN Bulletin Journal of Statistical Software Journal of Population Economics Risks Journal of Zhejiang University - Science A Journal of Time Series Analysis European Journal of Operation Research Econometrica Dependence Modeling Journal of Economic Behavior & Organization Entropy Sustainability Risk Analysis Journal of Statistical Computation and Simulation North American Actuarial Journal IEEE Transactions on Information Theory Remote Sensing Stochastic Processes & Applications Journal of Mathematical Economics Journal of Risk and Insurance PLOS One Journal of Theoretical Biology Bulletin de l'Association Mathématique du Québec International Journal of Mathematics in Operational Research Systems and Control Letters Applied Economics International Journal of Information Management Data Insight Big Data & Society ACM Computing Surveys Natural Hazards and Earth System Sciences; EGUsphere; Information Sciences Measurement (Journal of the International Measurement Confederation) Annals of Operations Research Information Sciences

Books (reviews)
MIT Press Springer Verlag SAGE Economica Cambridge University Press CRC Press

Grants & Scolarships
ANR (Agence Nationale pour la Recherche, France) AXA Research Fund FNR Luxembourg CORE program (Luxembourg) FRQNT (Fonds de Recherche du Québec - Nature & Technologie, Canada) FRS-FNRS (Fonds de la Recherche Scientifique, Belgique) MICTACS (Mathematics of Information Technology and Complex systems, Canada) NSA (National Security Agency - Mathematical Sciences Grant Program - U.S.A.) NSERC-CRSNG (Natural Sciences and Engineering Research Council, Canada) IVADO (Institut de valorisation des données, Canada) ESF (European Science Foundation) ANRT (Agence Nationale Recherche & Technologie, France) ISF (הקרן הלאומית למדע, Israel) SNSF-FNS (Swiss National Science Foundation) NWO (Nederlandse Organisatie voor Wetenschappelijk Onderzoek - Dutch Research Council) Research Grants Council (RGC) of Hong Kong