► Books (4)

  1. Cardot, H., Chagny, G., Cugliari-Duhalde, J., Dabo-Niang, S., Nerini, D., Roche, A., Saporta, J. (2025). Analyse de données fonctionnelles / Functional Data Analysis. JES, SFDS.

  2. Xu, J., Noor Azina Binti Ismail, N.A.B., Dabo-Niang, S., Ali Hassan, M.H., Hajiyev, A. (2024). The Eighteenth International Conference on Management Science and Engineering Management. Springer, Lecture Notes on Data Engineering and Communications Technologies.

  3. Mathematical Modeling and Study of Random or Deterministic Phenomena. Wiley. Link

  4. Dabo-Niang, S and Ferraty, F. (2008). Functional and Operatorial Statistics. Springer-Verlag, New York.

► Research papers (95)

  1. Jannin, A., Dabo-Niang, S., Dessein, A-F., et al. (2025). Metabolite biomarker discovery for pancreatic neuroendocrine tumors using metabolomic approach. European Journal of Endocrinology, 27 ; 192(4) :466-480. 10.1093/ejendo/lvaf055.

  2. Yap, Z.J., Pathmanathan, D.P., Dabo-Niang, S. (2025). Forecasting mortality rates with functional signatures.* ASTIN Bulletin. The Journal of the International Actuarial Association*. https ://doi.org/10.1017/asb.2024.38

  3. Si-Ahmed, I., Hamdad, L., Agonkoui, C., Kande, Y., Dabo-Niang, S. (2025). Principal Component Analysis of Multivariate Spatial Functional Data. Big Data Research. https ://doi.org/10.1016/j.bdr.2024.100504

  4. Moindjié, IA., Preda, C., Dabo-Niang, S. (2025). Fusion regression methods with repeated functional data. Computational Statistics and Data Aanalysis. https ://doi.org/10.1016/j.csda.2024.108069

  5. Ibrahimou, B., Sun, N., Dabo-Niang S. (2024). Assessing the multi-dimensional effects of air pollution on maternal complications and birth outcomes : A structural equation modeling approach. Hygiene and Environmental Health Advances. 12, 100113. https ://doi.org/10.1016/j.heha.2024.100113

  6. Doumun, S., Dabo-Niang, S., Zoueu, J. (2024). A Novel Unstained Blood Smears Multispectral Images Normalization for automatic and rapid diagnosis of malaria. International Journal of Imaging Systems and Technology. https ://doi.org/10.1002/ima.23182

  7. Tzung Hsuen, K. ; Pathmanathan, D. ; Otto, P. ; Dabo-Niang, S. (2024). A Markovswitching spatio-temporal ARCH model. STAT. https ://doi.org/10.1002/sta4.713

  8. Dabo-Niang, S., Frévent, C (2024). Uncovering Data Across Continua : An Introduction to Functional Data Analysis. AMS Notice(August, 2024). https ://www.ams.org/journals/notices/202407/rnoti-p869.pdf

  9. Pillay, A.B., Pathmanathan, D., Dabo-Niang, S., Abu, A., Omar, H. (2024). Functional data geometric morphometrics with machine learning for craniodental shape classification in shrews. Scientific Report 14, 15579. https ://doi.org/10.1038/s41598-024-66246-z

  10. Faye, P.A., Brunel, E., Claverie, T., Manou-Abi, S., and Dabo-Niang, S. (2024). Automatic geomorphological mapping using ground truth data with coverage sampling and random forest algorithms. Earth Sci Inform. https ://doi.org/10.1007/s12145-024-01347-x

  11. Frévent, C., Ahmed,. Dabo-Niang, S., Genin, M. (2024). A shared-frailty spatial scan statistic model for time-to-event data. Biometrical Journal. https ://doi.org/10.1002/bimj.202300200

  12. Dabo-Niang, S., Esteban, M-J., Guillopé, G., Martinez, C., M-F., Roy, M-F. (2024). Aspects of the gender gap in mathematics. European Mathematical Society Magazine. https ://euromathsoc.org/magazine/articles/178

  13. Kande, Y., Diogoul, N., Brehmer, P., Dabo-Niang, S,. Ngom, P., Perrot, Y. (2024). Demonstrating the relevance of spatial-functional statistical analysis in marine ecological studies : The case of environmental variations in micronektonic layers.Ecological Informatics, 81, https ://doi.org/10.1016/j.ecoinf.2024.102547.

  14. Moindjié, IA., Dabo-Niang, S., Preda, C. (2024) Classification of multivariate functional data on different domains with Partial Least Squares approaches. Stat Comput 34, 5. https ://doi.org/10.1007/s11222-023-10324-1

  15. Ahmed, M.S, Attouch, M.K, Dabo-Niang, S, Ndiaye, M. (2023). K-nearest neighbors method estimation of regression function for spatial dependent data. Journal of Spatial Econometrics. vol. 4(1), 1-34. https ://doi.org/10.1007/s43071-023-00041-2

  16. Dabo-Niang, S., Ah-Pine, J., Llop, P., Yao, A-F. (2023) Some results on statistics and functional data analysis. ESAIM : Proceedings and Surveys, Journées MAS, November 2023, Vol. 74, 2-18.

  17. Sun, N., Bursac, Z., Dryden, I. Lucchini, R., Dabo-Niang S., Ibrahimou, B. (2023). Bayesian spatiotemporal modelling for disease mapping : an application to preeclampsia and gestational diabetes in Florida, United States. Environ Sci Pollut Res. https ://doi.org/10.1007/s11356-023-29953-0

  18. Ringo, T-T, Nasini, S., Dabo-Niang S. (2023). An estimation approach for the influentialimitator diffusion. Computers and Operations Research, 159. https ://doi.org/10.1016/j.cor.2023.106315.

  19. Agonkoui, C., Dabo-Niang, S., Moussa. F-D. (2023). Multivariate Functional Principal Component Analysis for stratified data. Afrika Statistika. http ://dx.doi.org/10.16929/as/2022.3321.308

  20. Amouzay, H., Chakir, R., Dabo-Niang, S., El Ghiny, A. (2023). Structural Changes in Temperature and Precipitation in MENA Countries. Earth Syst Environ. https ://doi.org/10.1007/s41748-023-00344-2

  21. Si-Ahmed, I., Azeyou, M., Hamdad, L., Dabo-Niang, S. (2023). Functional, Multivariate Functional and Spatial PCA : Application to Covid-19 Data in the African Continent. In : Laouar, M.R., Balas, V.E., Lejdel, B., Eom, S., Boudia, M.A. (eds) 12th International Conference on Information Systems and Advanced Technologies ICISAT 2022. ICISAT 2022. Lecture Notes in Networks and Systems*, vol 624. Springer, Cham.

  22. Kanga, A-S., Ouagnina H., Dabo-Niang, S. (2023). On nonparametric conditional quantile estimation for non-stationary spatial processes. C. R., Math., Acad. Sci. Paris, 361, 847-852, https ://doi.org/10.5802/crmath.400.

  23. Bouka, S., Dabo-Niang, S., and Nkiet, G-M. (2023) On estimation and prediction in spatial functional linear regression model. Lithuanian Mathematical Journal. DOI : 10.1007/s10986-023-09586-z

  24. Frévent, C., Ahmed, M-S , Dabo-Niang, S., and Genin, M. (2023). Investigating spatial scan statistics for multivariate functional data. Journal of Royal Statistical Society C., 72, Issue 2, May 2023, Pages 450-475, https ://doi.org/10.1093/jrsssc/qlad017.

  25. Tchazino, T., Dabo-Niang, S and Diop, A (2022). Tail and quantile estimation for realvalued beta-mixing spatial data. Mathematical Methods of Statistics. DOI : 10.3103/S1066530722040044

  26. Dabo-Niang, S., Darwich, E., Hamdad, L., Thiam, B. (2022). Spatial Relative Risk of Upper Aerodigestive Tract Cancers Incidence in French Northern Region. SN Computer Science. DOI : https ://doi.org/10.1007/s42979-022-01426-0.

  27. C. Frévent, M.S. Ahmed, J. Soula, Z. Smida, L. Cucala, S. Dabo-Niang et M. Genin (2022). The R Package HDSpatialScan for Multivariate and Functional Spatial Scan Statistics. The R Journal. DOI : 10.32614/RJ-2022-045

  28. Kanga, A-S., Ouagnina H., Dabo-Niang, S, N’Guessan, A (2022). Asymptotic properties of nonparametric quantile estimation with spatial dependency. Statistica Neerlandica, 2022, DOI : 10.1111/stan.12284.

  29. Yacour, S., Dabo-Niang, S., El Ghini, A. (2022). Investigating Environmental Kuznets Curve for CO2 Emissions : A Cointegration Analysis for Morocco. Proceedings of the Sixteenth International Conference on Management Science and Engineering Management. Vol 2, 145, 506-525. Lecture Notes on Data Engineering and Communications Technologies, DOI : 10.1007/978-3-031-10385-8-36.

  30. Dabo-Niang, S., Thiam, B., Verdebout, T. (2022). Asymptotic efficiency of some nonparametric tests for location on hyperspheres. Statistics and Probability Letters, 188, 109524. DOI : https ://doi.org/10.1016/j.spl.2022.109524

  31. Kanga, S-H-A,.Hili, O., Dabo-Niang, S (2022). On Nonparametric Conditional Quantile Estimation for Non-stationary Random Fields. Afrika Statistika, 16 (4), 2021, 3009 - 3039. DOI : http ://dx.doi.org/10.16929/as/2021.3009.193.

  32. Ahmadian, B., Mbujamba, D., Gerbedoen, J-C., Kumemura, M., Fujita, H., Collard, D., Dabo-Niang, S., Lagadec, C., Tarhan, M-C (2022). Single cell classification using statistical learning on mechanical properties measured by mems tweezers. 2022 IEEE 35th International Conference on Micro Electro Mechanical Systems Conference (MEMS), Tokyo, Japan, 2022, pp. 317-320, doi : 10.1109/MEMS51670.2022.9699466.

  33. Gbogbo, A.Y, Kouakou, B-K, Dabo-Niang, S. Zoueu, J-T (2022). Predictive model for airborne insect abundance intercepted by a continuous wave Scheimpflug lidar in relation to meteorological parameters. Ecological Informatics, Vol 68. https ://doi.org/10.1016/j.ecoinf.2021.101528.

  34. Boumeddane, S. ; Hamdad, L. ; Haddadou, H. and Dabo-Niang, S. (2021). Dimensionality Reduction and Bandwidth Selection for Spatial Kernel Discriminant Analysis. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Vol. 2 : ICAART, ISBN 978-989-758-484-8 ISSN 2184-433X, p : 278-285. DOI : 10.5220/0010269002780285

  35. Boumeddane, S., Hamdad, L., Dabo-Niang, S., Haddadou, H. (2021). A Kernel Discriminant Analysis for Spatially Dependent Data. Distributed and Parallel Databases. 39 : 583-606. https ://doi.org/10.1007/s10619-020-07309-8.

  36. Vandewalle, V., Preda, C., Dabo-Niang, S. (2021). Clustering spatial functional data. Geostatistical Functional Data Analysis : Theory and Methods. J. Mateu and R. Giraldo (Eds). John Wiley and Sons, Chichester, UK. ISBN : 978-1-119-38784-8.

  37. Dabo-Niang, S., Ternynck, C., Thiam, B. and Yao, A-F. (2021). Non-parametric statistical analysis of spatially distributed functional data. Geostatistical Functional Data Analysis : Theory and Methods. J. Mateu and R. Giraldo (Eds). John Wiley and Sons, Chichester, UK. ISBN : 978-1-119-38784-8.

  38. Ahmed, M-S., Broze, L., Dabo-Niang, S., Gharbi, Z. (2021). Regression models for spatially distributed autoregressive functional data. Geostatistical Functional Data Analysis : Theory and Methods. J. Mateu and R. Giraldo (Eds). John Wiley and Sons, Chichester, UK. ISBN : 978-1-119-38784-8.

  39. Doumun, S., Dabo-Niang, S., Zoueu, J. (2020). Detection and segmentation of erythrocytes in multispectral label-free blood smear images for automatic cell counting. Journal of Spectral Imaging. https ://doi.org/10.1255/jsi.2020.a10

  40. Adekpedjou, A., Dabo-Niang, S. (2020). Semiparametric estimation with spatially correlated recurrent events. Scandinavian Journal of Statistics. https ://doi.org/10.1111/sjos.12480

  41. Ndiaye ; M., Dabo-Niang, S., Ngom, P., Thiam, N., Fall, M., Brehmer, P. (2020). Nonparametric prediction for spatial dependent functional data : Application to demersal coastal off Senegal. Mathematical Modeling and Study of Random or Deterministic Phenomena, Wiley. http ://www.iste.co.uk/book.php ?id=1601

  42. Alaya, M-A-B., Ternynck, C., Dabo-Niang, S., Chebana, F.,Ouarda, T.B.M.J.(2020). Change point detection of flood events using a functional data framework. Advances in Water Resources Vol ; 137, 103522 ; https ://doi.org/10.1016/j.advwatres.2020.103522

  43. Ahmed, M-S., Dabo-Niang, S., Genin, M., Hassan, A.A. (2019). Partially linear spatial probit models. Annals of ISUP. 63, fasc. 2-3, 2019, 71-96

  44. Boumeddane, S., Hamdad, L., Dabo-Niang, S., Haddadou, H. (2019). Spatial Kernel Discriminant Analysis : Applied for Hyperspectral Image Classification. ICAART (2), 184-191.

  45. Dabo-Niang, S., Thiam, B. (2019). Kernel regression estimation with errors-in-variables for random fields. Afr. Mat ; https ://doi.org/10.1007/s13370-019-00654-7

  46. Curceac, S., Ternynck, C., Ouarda, T.B.M.J., Chebana, F., Dabo-Niang, S. (2019). Short-term air temperature forecasting using Nonparametric Functional Data Analysis and SARMA models. Environmental Modelling and Software ; Vol ; 111, 394-408. DOI : 10.1016/j.envsoft.2018.09.017

  47. Hamdad, L., Benrabah, O., Dabo-Niang, S. (2018). Exploring spectral density estimation for spatial linear process with mixing innovations. Arab. J. Math ; https ://doi.org/10.1007/s40065-018-0227-3

  48. Giraldo, R., Dabo-Niang, S., Martinez, S. (2018). Statistical modeling of spatial big data : An approach from a functional data analysis perspective. Statistics and Probability Letters ; https ://doi.org/10.1016/j.spl.2018.02.025

  49. Ahmed, M.S, Attouch, M. and Dabo-Niang, S. (2017). Functional Binary Choice Models With Choice-Based Sampling. Econometrics and Statistics ; https ://doi.org/10.1016/j.ecosta.2017.07.001

  50. Amiri, A and Dabo-Niang, S. (2017). Density estimation over spatio-temporal data stream. Econometrics and Statistics ; https ://doi.org/10.1016/j.ecosta.2017.08.005.

  51. Soro, B., Hili, O., Niang, S. (2017). Asymptotic Properties of Longitudinal Weighted Averages for Strongly Mixing Data. Journal of Mathematics Research, 9(2), p65. doi :http ://dx.doi.org/10.5539/jmr.v9n2p65

  52. André, M., Dabo-Niang, S., Soubdhan, T. and Ould-Baba, H. (2016). Predictive spatiotemporal model for spatially sparse global solar radiation data. Energy, 111, 599-608. doi :10.1016/j.energy.2016.06.004

  53. Masselot, P., Dabo-Niang, S., Chebana, F. and Ouarda, T B.M.J. (2016). Streamflow forecasting using functional regression. Journal of Hydrology, 538C, 754-766. doi : 10.1016/j.jhydrol.2016.04.048

  54. Dabo-Niang, S., Ternynck, C., Yao, A.-F. (2016). Nonparametric prediction in the multivariate spatial context. Journal of Nonparametric Statistics, 10.1080/10485252.2016.1164313.

  55. Dabo-Niang, S, Guillas, S and Ternynck, C. (2016). Efficiency in Multivariate Functional Nonparametric Models with Autoregressive Errors. Journal of Multivariate Analysis, 147, 168-182, doi :10.1016/j.jmva.2016.01.007

  56. Ternynck, C., Ali Ben Alaya, M., Chebana, F., Dabo-Niang, S., Ouarda, T. B. M. J. (2016). Streamflow hydrograph classification using functional data analysis. Journal of Hydrometeorology, 17(1), DOI : 10.1175/JHM-D-14-0200.1.

  57. Amiri, A, Dabo-Niang and Yahaya, M (2016). Non-parametric recursive density estimation for spatial data. C. R., Math., Acad. Sci. Paris, 354 (2), 205-210 doi :10.1016/j.crma.2015.10.010.

  58. Bouka, S., Dabo-Niang, S., Nkiet, G-M (2015). Non-parametric level set estimation for spatial data. Advances and Application in Statistics, 46 (2), 119-158.

  59. Dabo-Niang, Ternynck, C., Yao, A.-F. (2015). A new spatial regression estimator in the multivariate context. C. R., Math., Acad. Sci. Paris, 353, 635-639. DOI10.1016/j.crma.2015.04.004

  60. Dabo-Niang, S, Kaid, Z. and Laksaci, A (2015). On spatial conditional quantile estimation for a functional regressor. Advances in Statistical Analysis, 2, 131-160. DOI 10.1007/s10182-014-0233-5

  61. Dabo-Niang, S., Hamdad, L., Ternynck, C., Yao, A.-F. (2014). A kernel spatial density estimation with applications to spatial clustering and Monsoon Asia Drought Atlas analysis. SERRA, 28, 2075-2099.

  62. Dabo-Niang, S ; Abdi, S ; Abdi, A, and Diop, A. (2014). Consistency of a nonparametric conditional mode estimator for random fields. Statistical Methods and Application. DOI : 10.1007/s10260-013-0239-2.

  63. Dabo-Niang, S and Yao, A-F. (2013). Spatial kernel density estimation for functional random variables. Metrika. 76(1) :19-52.

  64. Dabo-Niang, S, Kaid, Z. and Laksaci, A (2012). Spatial conditional quantile regression : weak consistency of a kernel estimate. Revue Roum Math Pures Appl, 4, 311-339.

  65. Dabo-Niang, S et Zoueu, J. (2012). Using kriging to resolve malaria-infected erythrocyte contents. Journal of Microscopy. DOI : 10.1111/j.1365-2818.2012.03637., 247 (3), 240- 251.

  66. Dabo-Niang, S, Kaid, Z. and Laksaci, A (2012). On spatial conditional mode estimation for a functional regressor. Statistics and probability letters, 82 (2012) 1413-1421.

  67. Chebana, F, Dabo-Niang, S and Ouarda, T. (2012). Explanatory functional flood frequency analysis. Water Resources Research, 48, W04514, doi :10.1029/2011WR011040.

  68. Dabo-Niang, S and Laksaci, A. (2012). Nonparametric quantile regression estimation for functional dependent data. Communication in Statistics : Theory and Methods. 41, 1254-1268.

  69. Dabo-Niang, S, Rachdi M and Yao, A-F. (2011). Spatial kernel regression estimation and prediction for functional random fields. Far east journal of Statistics. Volume 37, Issue 2, Pages 77 - 113.

  70. Abdi A, Abdi, S, Dabo-Niang, S and Diop, A. (2011). Asymptotic normality of a nonparametric conditional quantile estimator for random fields. Advances in Decision Sciences. Article ID 462157, doi :10.1155/2011/462157.

  71. Dabo-Niang, S, Kaid, Z. and Laksaci, A (2011). Sur la régression quantile pour variable explicative fonctionnelle : Cas des données spatiales. C. R., Math., Acad. Sci. Paris. Vol 349, 23-24, 1287-1291.

  72. Benrabah, O, Dabo-Niang S. et Hamdad, L. (2010). Kernel density estimation for linear processes with dependent innovations. Journal of Statistics : Advances in Theory and Applications, Vol 4, 1, 41-72.

  73. Dabo-Niang, S, Francq, C and Zakoian, J-M. (2010). Combining parametric and nonparametric approaches for time series prediction. JASA, Vol 105 (492), 1554-1565.

  74. Abdi A, Abdi, S, Dabo-Niang, S and Diop, A. (2010). Estimation non-paramétrique du mode conditionnel spatial. C. R., Math., Acad. Sci. Paris. Vol. 348 (13-14), 815-819.

  75. Dabo-Niang, S and Thiam, B. (2010). L1 consistency of a kernel estimate of spatial conditional quantile. Statistics and probability letters, Vol. 80 (17-18), 1447-1458.

  76. Abdi, S, Abdi, A, Dabo-Niang, S et Diop, A. (2010). Consistency of a nonparametric conditional quantile estimator for random fields. Mathematical Methods and Statistics, 2010, Vol. 19, No. 1, 1-21.

  77. Dabo-Niang, S and Laksaci, A. (2010). Note on conditional mode estimation for functional dependent data. Statistica, Vol LXX (1), 83-94.

  78. Bensaid, N and Dabo-Niang, S. (2010). Frequency polygons for continuous random fields. Stochastic Processes and Statistical Inference, 13,1, 55-80.

  79. Dabo-Niang, S, Yao, A-F, Pischedda, L, Cuny, P and Gilbert, F. (2010). Spatial mode estimation for functional random fields with application to bioturbation problem. Stochastic Environmental Research and Risk Assessment, 24, 4, 487-497.

  80. Dabo-Niang, S and Guillas S (2010). Functional semi-parametric partially linear model with autoregressive errors. Journal of multivariate analysis, 101, 2, 307-315.

  81. Dabo-Niang, S and Rhomari, N (2009). Kernel regression estimate in a Banach space. Journal of statistical planning and inference, 139, 1421-1434.

  82. Basse, M, Dabo-Niang, S and Diop, A (2008). Kernel density estimation for functional random fields. Pub. Inst. Stat. Univ. Paris, LII, 1-2, 91-108.

  83. Deru, X., Champarnaud, L., Dabo, S., and Florent, G. (2007). Chronology, ceramics and statistics, Proceedings of the Congress of Langres, SFECAG, 49-60.

  84. Dabo-Niang, S and Laksaci, A (2007). Non-parametric conditional mode estimate with explanatory functional variable. Pub. Inst. Stat. Univ. LI, 3, 27-42.

  85. Dabo-Niang, S and Yao, A-F (2007). Spatial kernel regression estimation. Mathematical Methods of Statistics, Vol 16, No 4, 1-20.

  86. Dabo-Niang, S. and Laksaci, A. (2007). Estimation of non-parametric conditional mode for explanatory functional variable. C.R., Math., Acad. Sci. Paris, 344, 49-52.

  87. Dabo-Niang, S., Ferraty, F. and Vieu, P. (2007). On the using of modal curves for radar waveforms classification. Computational statistics and data analysis, Vol 51, 4878-4890.

  88. Dabo-Niang, S., Ferraty, F. and Vieu, P. (2006). Mode estimation for functional random variable and its application for curves classification. µFar East Journal of Theoretical Statistics*. Vol 18, No. 1 (2006), pp 93 - 119.

  89. Dabo-Niang, S, Ferraty, F and Vieu, P. (2004). Nonparametric unsupervised classification of satellite wave altimeter forms. In Proceedings in Computational Statistics, Ed, J, Antoch, Physica-Verlag, Heidelberg New-York, p : 879-886.

  90. Dabo-Niang, S ; Ferraty, F and Vieu, P. (2004). Mode estimation in a functional space. C.R.Acad. Sci. Paris, Ser I. 339, 659-662.

  91. Dabo-Niang, S. (2004). Kernel density estimator in an infinite dimensional space with a rate of convergence in the case of diffusion process. Applied Mathematical Letters, Vol 17, 4, p : 381-386.

  92. Dabo-Niang, S. (2004). Density estimation by orthogonal series in an infinite dimensional space : Application to processes of diffusion type. Journal of Nonparametric Statistics, Vol 16, 1-2, p : 171-186.

  93. Dabo-Niang, S. (2003). Density estimation in a separable metric space. Pub. Inst. Stat. Univ. Paris, Vol. XXXXVII, fasc. 1-2, 3-21.

  94. Dabo-Niang, S and Rhomari, N. (2003). Non-parametric estimation of regression with explanatory variable in a metric space. C.R.Acad. Sci. Paris, Ser I. 336, 75-80.

  95. Dabo-Niang, S. (2002). Estimation of probability density in infinite dimension : Application to diffusion processes. C.R.Acad. Sci. Paris, Ser I.334, 213-216.

► Articles under revision or submitted (3)

  1. Nasini, S., Erdemlioglu, D., Ding, H., Dabo-Niang, S. (2024). Retrospective Bayesian Estimation for Multinational Pandemic Outbreaks.

  2. Pathmanathan, D., Dabo-Mbenard, I., Tzung Hsuen, K.,Hassan, A.A. and Dabo-Niang, S. (2024). Functional space time series forecasting and application to age-specific mortality rates.

  3. BenSaber, A., Dabo-Niang, S., Karoui, A. (2024). Multivariate nonparametric regression by least squares Jacobi polynomials approximations.

► Some works in progress (3)

  1. Cheok, M., Dabo-Niang, S., Nasini, S., Thiam, B. (2024). Integrated AI-based pharmacodynamic modelling for pediatric acute myeloid leukemia.

  2. Ahmadian, Agonkoui, C., Dabo-Niang, I-M, B.,Collard, D., Tarhan, M-C., Dabo-Niang, S (2024). Single cell classification for cancer cell identification.

  3. Dabo-Niang, S., El Ghini, A. and Yacour, S. (2023). Spatial-temporal analysis of impact of economic growth on the environment in Africa.

► Softwares (1)

  1. Frévent, C., Ahmed, M-S, Soula, J., Smida, Z., Cucala, L., Dabo-Niang, S., Genin, M. (2021). Multivariate and Functional Spatial Scan Statistics. R Package. HDSpatialScan

► Research projects

◉ Member of projects developed within the framework of the SIRIC Lille Nord de France.

  1. 2011 - 2015 : New risk factors for cancers of the upper aerodigestive tract in the Nord-Pas de Calais region.

Budget : 126.940 euros. Financing: CPER.

  1. 2011 - 2014 : Determinants of the consultation time in cancers of the upper digestive tract (DEREDIA).

Budget : 305.435 euros. Funding: National Cancer Institute.

◉ 2015 - 2017 : Principal Investigator (PI) “Determination of recurrence factors of digestive cancers”. Funding: SIRIC Lille Nord de France, University of Lille, Northern League Against Cancer.

Budget : 50.000 euros.

◉ 2011 - 2012 : Principal Investigator (PI) on the French side of the project “Study of hydrological variables in the framework of the analysis of functional data (EVHADF)”.

Total budget (French and Quebec): 23.264 euros. Funding: CPCFQ (Franco-Québécois Cooperation).

◉ 2009 - 2011 : Member of the project: “Dynamics of the Economy of Art and Culture (DEAC)”

Budget : 30.000 euros. Financing CPER.

◉ 2010 - 2012 : Member of the project: “Socio-economic mapping of live performance”.

Budget : 34.951 euros. Funding : Ministry of Culture.

◉ 2013 - 2015 : Principal Investigator (PI) on the French side of the project “Modeling and hydrological forecasting with functional approaches, the cases of Quebec and France (MPHAQF)”.

Total budget (French and Québécois) : 28.130 euros. Funding : CPCFQ (Franco-Québécois Cooperation).

◉ January 2015 : Member of the Simerge Project http: //mistis.inrialpes.fr/simerge/.

◉ 2018 - 2021 : Member of the project “Role of socioeconomic and environmental inequalities in gastroesophageal cancers”.

Total budget : 300.000 euros. Submitted.

◉ PI of the industrial project with the company “Semences de France”.

Budget : 9.114 euros.

◉ 2018 - 2021 : PI of the French side of the Franco-Marocco project on “Economic Growth and Environmental Impacts”. Funding : Moroccan and French governments.

Budget : 12.000 euros.

◉ 2019 - 2021 : Member of the project ” Role of socioeconomic and environmental inequalities in gastro- esophageal cancers”.

Budget : 300.000 euros.

◉ 2021 - 2023 : Co-PI of the project “Impact du contexte pand ́emique de COVID-19 sur les conduites suicidaires et leur prise en charge”.

Budget : 439.088 euros.

◉ 2021 - 2024 : PI of the project ” PATH (PArcours paTient en milieu Hospitalier)” between INRIA and CHU of Lille.

Budget : 150.000 euros.

◉ 2021 - 2022 : PI of the project ” Projet interactif de visualisation des indicateurs de suivi du SCoT de Lille Métropole”, 2021.

Budget : 12.825 euros.

◉ 2022 - 2024 : Co-PI of the ANR project CYTOMEMS “Smart MEMS Instrumentation for Biophysical flow Cytometry with Statistical Learning”.

Budget : 545.608 euros.

◉ 2024 - 2027 : Co-PI of INCA project “Role of calcium signaling in acute myeloid leukemia and the immunological synapse”.

Budget : 594.891 euros.

◉ 2024 - 2028 : Member of EN-HOPE SMART4CBT, SIRIC project “East North-Hematology Oncology PEdiatric consortium offering a research program of Social sciences, Microenvironment and multiomics Analyses in RadioTherapy resistance For Children Brain Tumors”.

Budget : 3.000 K-euros.

◉ 2023 - 2024 : PI of the PHC Ulysses project “Ireland and France Need Healthier Air for healthier Lungs-the Evidence”; between University College Dublin and University of Lille.

Budget : 5k euros.

◉ 2024 - 2025 : PI of the Programme Hubert Curien “Estimation with preliminary test, penalization in high dimension with applications”; between University Libre of Brussels and University of Lille.

Budget : 3k euros.

◉ 2024 - 2027 : PI of France-Afrique Network for Mathematics of Sustainable Planet Earth (FANE- MATH-PE).

Budget : 300k euros.