DEACONU Madalina

Position Inria senior scientist
Research group Probabilities and statistic
Research fields

 

  • Stochastic modeling and data analysis
  • Probabilistic approach of coagulation / fragmentation models
  • Numerical methods for diffusions’ hitting times
  • Stochastic methods for linear and non-linear PDEs
Keywords
  • Stochastic modeling
  • Probabilistic numerical methods
  • Spatio-temporal stochastic processes
Mail

IECL – Site de Nancy
Faculté des sciences et Technologies
Campus, Boulevard des Aiguillettes
54506 Vandœuvre-lès-Nancy

Email madalina.deaconu@univ-lorraine.fr
Phone number 0372745400
Office 215

I am Deputy Head of Science (DSA) at Centre Inria de l’Université de Lorraine

I am the Head of the PASTA research team at Centre Inria de l’Université de Lorraine. Know more on PASTA.

I am member of the Comité de programme Géophysique du RT CNRS “Terre & Energies”.

News

Main publications

  • M. Deaconu et A. Lejay, Probabilistic representations of fragmentation equations, Probability Surveys 20 (2023), 226-290, HAL
  • M. Deaconu et S. Herrmann, Initial-boundary value problem for the heat equation – A stochastic algorithm, The Annals of Applied Probability, 28:3 (2018), 1943-1976, HAL
  • L.Beznea, M.Deaconu et O.Lupascu, Stochastic equation of fragmentation and branching processes related to avalanches, Journal of Statistical Physics 162 (2016), 824-841, HAL

Publications

  1. G. Agazzotti, M. Deaconu et A. Lejay, Long time asymptotic behavior of a self-similar fragmentation equation, Soumis (2024), HAL
  2. M. Deaconu et S. Herrmann, Strong approximation of particular one-dimensional diffusions, Discrete and Continuous Dynamical Systems Series B 29:4 (2024), 1990-2017, HAL
  3. M. Deaconu et A. Lejay, Probabilistic representations of fragmentation equations, Probability Surveys 20 (2023), 226-290, HAL
  4. C. Reype, R.S. Stoica, A. Richard et M. Deaconu, HUG model: an interaction point process for Bayesian detection of multiple sources in groundwaters from hydrochemical data, Soumis (2023), HAL
  5. M. Deaconu et S. Herrmann, Strong approximation of Bessel processes, Methodology and Computing in Applied Probability, 25:1 (2023),  11 HAL
  6. C. Reype, R.S. Stoica, D. Gemmerlé, A. Richard et M. Deaconu, Hug model: parameter estimation via the ABC Shadow algorithm, RING Meeting, 2023, HAL
  7. L. Lesage, M. Deaconu, A. Lejay, J. Meira, G. Nichil et R. State, Hawkes processes framework with a Gamma density as excitation function: application to natural disasters for insurance, Methodology and Computing and Applied Probability 24 (2022), 2509-2537, HAL
  8. R. S. Stoica, M. Deaconu, A. Philippe et L. Hurtado, Shadow Simulated Annealing: a new algorithm for approximate Bayesian inference of Gibbs point processes, METMA X, Proceedings of the 10th International Workshop on Spatio-Temporal Modelling, Lleida (spain) 1-3 June 2022 (2022), 45-51.
  9. M. Deaconu et O. Lupascu-Stamate, Asymptotic behaviour of a one-dimensional avalanche model through a particular stochastic process, Soumis (2022) HAL
  10. L. Lesage, M. Deaconu, A. Lejay, J. Meira, G. Nichil et R. State, A Recommendation System For Insurance Built With A Multivariate Hawkes Process Based On Customers’ Life Events, Soumis, (2021), HAL
  11. R. S. Stoica, M. Deaconu, A. Philippe et L. Hurtado, Shadow Simulated Annealing: a new algorithm for approximate Bayesian inference of Gibbs point processes, Spatial Statitstics 43 (2021), HAL
  12. L. Beznea, M. Deaconu et O. Lupascu-Stamate, Scaling property for branching fragmentation processes related to avalanches, Applications of Mathematics and Informatics in Natural Sciences and Engineering, AMINSE 2019, Springer Proceedings in Mathematics & Statistics 334 (2020), 37–47, HAL
  13. L. Lesage, M. Deaconu, A. Lejay, J.A. Meira, G. Nichil et R. State, A Recommendation System For Car Insurance, European Actuarial Journal, Springer, 10 (2020), 377-398, HAL
  14. C. Reype, A. Richard, M. Deaconu et R.S. Stoica, Bayesian statistical analysis of hydrogeochemical data using point processes: a new tool for source detection in multicomponent fluid mixtures, RING Meeting 2020, 2020, HAL
  15. L. Beznea, M. Deaconu et O. Lupascu, Numerical approach for stochastic differential equations of fragmentation; application to avalanches, Mathematics and Computers in Simulation 160 (2019), 111-125, HAL
  16. P. Charton, M. Deaconu et A. Lejay, A stochastic approach for controlling a wind farm with storage unit (2019). Preprint.
  17. M. Deaconu et S. Herrmann, Initial-boundary value problem for the heat equation – A stochastic algorithm, The Annals of Applied Probability, 28:3 (2018), 1943-1976, HAL
  18. M. Deaconu, A. Lejay et K. Salhi, Approximation of CVaR minimzation for hedging under exponential-Lévy models, Journal of Computational and Applied Mathematics 326 (2017), 171-182, HAL
  19. M. Deaconu et S. Herrmann, Simulation of hitting times for Bessel processes with non integer dimension, Bernoulli 23 (2017), 3744-3771, HAL
  20. M. Deaconu, S. Herrmann et S. Maire, The walk on moving spheres: a new tool for simulating Brownian motion’s exit time from a domain, Mathematics and Computers in Simulation 135 (2017), 28-38, HAL
  21. B. Dumortier, E. Vincent et M. Deaconu, Recursive Bayesian estimation of the acoustic noise emitted by wind farms, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2017, HAL
  22. B. Dumortier, E. Vincent et M. Deaconu, Recursive Bayesian estimation of the acoustic noise emitted by wind farms, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2017, HAL
  23. B. Dumortier, E. Vincent et M. Deaconu, Effcient optimisation of wind power under acoustic constraints (2017), Preprint. HAL
  24. K. Salhi, M. Deaconu, A. Lejay, N. Champagnat et N. Navet, Regime switching model for financial data: empirical risk analysis, Physica A, 461 (2016), 148-157, HAL
  25. L.Beznea, M.Deaconu et O.Lupascu, Stochastic equation of fragmentation and branching processes related to avalanches, Journal of Statistical Physics 162 (2016), 824-841, HAL
  26. N. Champagnat, M. Deaconu et A. Lejay, Méthodes de calcul de la Value-at-Risk et de la Conditional Value-at-Risk, 2016. Rapport de contrat Alphability – Equipe Tosca Nancy, HAL
  27. L. Beznea, M. Deaconu et O. Lupascu, Branching processes for the fragmentation equation, Stochastic Processes and their Applications, 125 (2015), 1861-1885, doi 10.1016/j.spa.2014.11.016, HAL
  28. B. Dumortier, E. Vincent et M. Deaconu, Acoustic Control of Wind Farms, EWEA 2015 – European Wind Energy Association, Paper and Poster award, 2015, HAL
  29. N. Champagnat, M. Chikhaoui, M. Deaconu et A. Lejay, Gestion de risque de portefeuille : estimation de la VaR et la CVaR, 2015. Rapport de contrat Alphability – Equipe Tosca Nancy
  30. N. Champagnat, M. Deaconu, A. Lejay et A. Bedoui, Analyse de dépendance d’actifs financiers par la méthode des copules, 2014. Rapport de contrat Alphability / Equipe Tosca Nancy, HAL
  31. M. Deaconu et S. Herrmann, Hitting time for Bessel processes—walk on moving spheres algorithm (WoMS), The Annals of Applied Probability, 23:6 (2013), 2259–2289, HAL
  32. N. Champagnat, M. Deaconu, A. Lejay et K. Salhi, Mesure de risque : détection du régime de crise et calcul de la Value-at-Risk, 2013. Rapport de contrat Alphability / Equipe Tosca Nancy, HAL
  33. S. Boukherouaa, N. Champagnat, M. Deaconu et A. Lejay, Mesure de risques : calcul de la Value-at-Risk et application à la gestion deportefeuilles, 2013. Rapport de contrat Alphability / Equipe Tosca Nancy, HAL
  34. N. Champagnat, M. Deaconu, A. Lejay, N. Navet et S. Boukherouaa, An empirical analysis of heavy-tails behavior of financial data: The case for power laws (2013). Preprint. HAL  Preprint.
  35. M. Deaconu, S. Herrmann et A. Lejay, Sur le problème de la stratégie optimale de couverture d’une centrale  électrique, 2011. Rapport de contrat GDF Suez Louvain la Neuve / Equipe Tosca Nancy, HAL
  36. S. Zein, A. Lejay et M. Deaconu, An effcient algorithm to simulate a Brownian motion over irregular domains, Communications in Computational Physics 8:4 (2010), 901–916, HAL
  37. M. Deaconu et A. Lejay, Simulation of diffusions by means of importance sampling paradigm, The Annals of Applied Probability 20:4 (2010), 1389–1424, HAL
  38. M. Deaconu et A. Lejay, Problème d’ éclatement de tuyaux : approches Monte Carlo, 2010. Rapport de contrat GDF Suez-La Plaine, Saint Denis / Equipe Tosca Nancy, HAL
  39. A. Bergaoui, M. Deaconu, M.Z. Ghazai, I. Henchiri, S. Herrmann, A. Lejay, V. Reutenauer, D. Talay, E. Tanré et Y. Wang, Méthodes de réduction de variance originales et de simulation exacte de prix et de grecques en finance, 2009. Rapport de contrat Calyon / Equipe Tosca, HAL
  40. M. Deaconu, Processus stochastiques associés aux équations d’évolution linéaires ou non-linéaires et méthodes numériques probabilistes, Habilitation a diriger des recherches, Université Henri Poincaré – Nancy 1, France, 2008, HAL
  41. M. Deaconu et A. Lejay, Simulation of exit times and positions for Brownian motions and Diffusions, Sixth International Congress on Industrial Applied Mathematics (ICIAM07) and GAMM Annual Meeting, Zurich 2007, PAMM 7:1 (2008), 1081401–1081402, HAL
  42. M. Deaconu et A. Lejay, A random walk on rectangles algorithm, Methodology and Computing in Applied Probability 8:1 (2006), 135–151, HAL
  43. M. Deaconu, N. Fournier et E. Tanré, Rate of Convergence of a Stochastic Particle System for the Smoluchowski coagulation equation, Methodololy and Computing in Applied Probability 5:2 (2003), 131–158, HAL
  44. M. Bossy, M. Deaconu et E. Tanré, Rapport de fin de collaboration EDF / Inria sur un modèle d’équilibre de production pour la détermination du prix spot, 2003. Rapport de contrat EDF / Projet Omega.
  45. M. Deaconu et N. Fournier, Probabilistic approach of some discrete and continuous coagulation equations with diffusion, Stochastic Processes and Their Applications 101 (2002), 83–111, lien
  46. M. Deaconu, N. Fournier et E. Tanré, A pure jump Markov process associated with the Smoluchowski’s coagulation equation, The Annals of Probability 30:4 (2002), 1763–1796, HAL
  47. M. Deaconu et E. Tanré, A generalization of the connection between the additive and multiplicative solutions for the Smoluchowski’s coagulation equation, Monte Carlo Methods and Applications 7:1-2 (2001), 141–147, HAL
  48. M. Deaconu, N. Fournier et E. Tanré, A pure jump Markov process associated with the Smoluchowski’s coagulation equation, Stochastic Numerics 2001, a Workshop on numerical methods for stochastic differential equations, Feynman-Kac representations and paths integrals, Zurich (2001).
  49. M. Deaconu et E. Tanré, Smoluchowski’s coagulation equation : probabilistic interpretation of solutions for constant, additive and multiplicative kernels, Annali della Scuola Normale Superiore di Pisa, Série IV XXIX:3 (2000), 549–580, HAL
  50. M. Deaconu, M. Gradinaru et J.R. Roche, Sojourn time of some reflected Brownian motion in the unit disk, Probability and Mathematical Statistics 20:1 (2000), 19–38, HAL
  51. M. Deaconu, Rapport de fin de collaboration EDF / Inria, Etude de la capacité des centrales  électriques, 2000. Rapport de contrat EDF / Projet Omega.
  52. M. Deaconu et S. Wantz, Processus non linéaire autostabilisant réfléchi, Bulletin des Sciences Mathématiques 122:7 (1998), 521–569.
  53. M. Bossy, M. Deaconu, J.P. Minier et D. Talay, Rapport de fin de collaboration EDF / Inria sur la simulation d’écoulements diphasiques turbulents, 1998. Rapport de contrat EDF / Projet Omega.
  54. M. Deaconu, Processus stochastiques et équations aux dérivées partielles. Applications des espaces de Besov aux processus stochastiques, Thèse de doctorat, Université Henri Poincaré – Nancy 1, France, 1997, HAL
  55. M. Deaconu et S. Wantz, Comportement des temps d’atteinte d’une diffusion fortement rentrante, Séminaire de Probabilités XXXI. Editeurs : J. Azéma, M. Emery, M. Yor. Lecture Notes in Mathematics 1655 (1997), 168–175, HAL
  56. M. Deaconu, Régularité du mouvement brownien itéré, C.R. Acad. Sci. Paris 323, Série I (1996), 933–938.
  57. M. Deaconu et S. Wantz, Comportement des temps d’atteinte d’une diffusion fortement rentrante, C.R. Acad. Sci. Paris 322, Série I (1996), 757–762.
  58. M. Deaconu et A. Kamont, Approximation by Tensor Product Neural Networks, 1995. Prépublication de l’Institut Elie Cartan, Nr. 20.
  59. M. Deaconu et B. Roynette, Besov Regularity for the Solution of Walsh Equation, 1995. Prépublication de l’Institut Elie Cartan, Nr. 6.

    Industrial parternship

    • Le Foyer Luxembourg and SnT University of Luxembourg, 2018-2022. Coordinator for PASTA.

    Collaborations et  international projects projets

    • Cristina Zucca (University of Torino).
    • Ernesto Mordecki (Centro de Matematica, University of the Republic of Uruguay).
    • Lucian Beznea (IMAR, Bucharest) and Oana Lupascu-Stamate (ISMMA Bucharest).

    Collaborations in France and research projects

    • Samuel Herrmann (University of Burgundy).
    • Caroline Le Bouteiller (INRAE Grenoble).
    • Courses Modélisation Stochastique , Master 2 IMSD, Université de Lorraine et Ingénierie Mathématique, 3A, École des Mines de Nancy
    • Cours Équations Différentielles Stochastiques – Résolution Numérique et Applications, 3A, École des Mines de Nancy
    • Cours Simulation de variables aléatoires, 2A, École des Mines de Nancy
    • Cours Monte Carlo Simulation, Master 1 – IFM – Ingénierie Financière de Marché, Université de Lorraine, Faculté de Droit, Sciences Économiques et Gestion

    – Deputy Head of Science (DSA) at Centre Inria de l’Université de Lorraine, since Jnauary 2022.

    – Head of the research Inria team  PASTA – Processus Aléatoires Spatio-Temporels et leurs Applications  joint research project with Université de Lorraine and CNRS. PASTA is located at IECL.

    – Member of the  Commission d’Évaluation d’Inria,  since January 2022

    – Member of Bureau du Comité des Projets (BCP), Centre Inria de l’Université de Lorraine, since 2011.

    – Member of Comité des Projets, Centre Inria de l’Université de Lorraine, since June 2005.

    – Head of  Fédération Charles Hermite, research federation between  CNRS and Université de Lorraine, which contains three research  laboratories and UMRs :  CRAN (Automatic), IECL (Mathematic) et  LORIA (Computer Science), 1//01/2018 – 31/12/2022.

    – Member of Bureau and Conseil du Pôle Scientifique AM2I (Automatique, Mathématiques, Informatique et leurs Interactions), Université de Lorraine,  1/01/2018 – 31/12/2022.

    – Member of Conseil de laboratoire de l’Institut Elie Cartan de Lorraine,  1/01/2018 – 31/12/2022.

    Curriculum Vitae