Camila de Souza

Assistant Professor
Director of WDSS
Office: WSC 225
Phone: 519-661-2111 x83618



Western Data Science Solutions  (WDSS)SS 

Graduate Student Supervision

  • Zahra AghahosseinalisShirazi (PhD)
  • Pedro Assuncao Rangel (MSc)
  • Ana Carolin Da Cruz (PhD)
  • Chengqian Xian (PhD)

Research interests:

My research program consists of developing new statistical methods to analyze large and complex data structures arising from various areas in the Natural Sciences, Health, and Engineering. I conduct research on techniques involving clustering, hierarchical mixture models, mixed effect models, hidden Markov models, nonparametric regression, semi-parametric models, expectation-maximization (EM) algorithm, and Bayesian variational inference. I am particularly interested in applications comprising single-cell sequencing data, and electrical energy consumption data.


Safinianaini, N., de Souza, C. P. E., Roth, A., Lagergren, J., CopyMix: Mixture Model Based Single-Cell Clustering and Copy-Number Calling using Variational Inference. Preprint available at BioRxiv:

Sousa, P.H.T.O., de Souza, C.P.E., Dias, R., Bayesian Adaptive Selection of Basis Functions for Functional Data Representation. Under review. Preprint available at ArXiv:

Franco, G., de Souza, C. P. E., and Garcia, N., Aggregated functional data model applied on clustering and disaggregation of UK electrical load profiles. Accepted and to appear in the  Journal of the Royal Statistical Society: Series C (Applied Statistics). Preprint available at ArXiv: 

Chies-Santos, A. L., de Souza, R. S., Caso, J. P., Ennis, A. I., de Souza, C. P. E., Barbosa, R. S., et al., (2022) J-PLUS: A catalogue of globular cluster candidates around the M81/M82/NGC3077 triplet of galaxies. Monthly Notices of the Royal Astronomical Society (MNRAS), 516, 1320–1338.

Moazamigoodarzi, S., Na, W., Najafi, M. R., de Souza, C., (2022) Spatiotemporal bias adjustment of IMERG satellite precipitation data across Canada, Advances in Water Resources, Volume 168, 104300,

Kobara, Y. M., Rodrigues, F. F., de Souza, C. P.E., Stanford, D. A. (2022). Intensive care unit/step-down unit queuing game with length of stay decision. Operations Research for Health Care, 100349, 

Aghahosseinalishirazi, Z., da Silva, J. P., de Souza, C. P. E., (2022) Parameter estimation for grouped data using EM and MCEM algorithms, Communications in Statistics – Simulation and Computation. Published online at 

de Cássia Almeida Vieira, R., Silveira, J. C. P., Paiva, W. S., de Oliveira, D. V., de Souza, C. P. E., Santana-Santos, E.,  de Sousa, R. M. C. (2022). Prognostic Models in Severe Traumatic Brain Injury: A Systematic Review and Meta-analysis. Neurocritical Care, 1-16,

Sills, D. M. L., Durfy, C. S., de Souza, C. P. E. (2022). Are significant tornadoes occurring later in the year in southern Ontario? Geophysical Research Letters, 49, 

Chen, D., Randhawa, G.S., Soltysiak, M.P.M., de Souza, C.P.E., Kari, L., Singh, S.M., Hill, K.A. (2022), SomaticSimu: A mutational signature simulator. Bioinformatics, 38 (9), 

Evelyn Vingilis, Jane S. Seeley, Patricia Di Ciano, Christine Wickens, Robert E. Mann, Gina Stoduto, Tara Elton-Marshall, Branka Agic, Camila de Souza, André McDonald, Jason Gilliland, Tanya Charyk Stewart, (2021) Systematic Review of the Effects of Cannabis Retail Outlets on Traffic Collisions, Fatalities and other Traffic-related Outcomes. Journal of Transport & Health, Vol. 22. 

Adjei, P., Sethi, N. S., de Souza, C.P.E. and Capretz, M.A.M., (2020) Energy Disaggregation using Multilabel Binarization and Gaussian Naive Bayes Classifier. Proceeding of the 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON).

Safinianaini, N., de Souza, C. P. E., Bostrom, H., and Lagergren, J., (2020) Orthogonal Mixture of Hidden Markov Models. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2020. Lecture Notes in Computer Science, vol 12457. Springer, Cham.

P. E. de Souza C*, Andronescu M*, Masud T, Kabeer F, Biele J, et al. (2020) Epiclomal: Probabilistic clustering of sparse single-cell DNA methylation data. PLOS Computational Biology 16(9): e1008270. *Authors contributed equally to this work.

Randhawa, Gurjit S., Maximillian P.M. Soltysiak, Hadi El Roz, Camila P. E. de Souza, Kathleen A. Hill, and Lila Kari, Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study. PLOS ONE. 

Shirazi, R., de Souza, C. P. E., Kashef, R. and Rodrigues, F. F., (2020) Deep Learning in the Healthcare Industry: Theory and Applications, Book Chapter. In Computational Intelligence and Soft Computing Applications in Healthcare Management Science (pp. 220-245). IGI Global.

Santos, E.S., de Morais Oliveira, C.D., Menezes, I.R.A., do Nascimento, E.P., Correia, D.B., de Alencar, C.D.C., de Fátima Sousa, M., Lima, C.N.F., Monteiro, Á.B., de Souza, C.P.E. and de Araújo Delmondes, G., 2019. Anti-Inflammatory Activity of herb products from Licania rigida Benth. Complementary Therapies in Medicine.

Zhang, A. W., McPherson A., Milne, K., Kroeger, D. R., Hamilton, P. T., Miranda, A., Funnell, T., Little, N., de Souza C. P. E., Laan, S., LeDoux, S., Cochrane, D. R., Lim, J. L. P., Yang, W.,  Roth, A., et al., (2018) Interfaces of malignant and immunologic clonal dynamics in ovarian cancer. Cell.

Farahani, H.*, de Souza, C. P. E.*, Billings, R.*, Yap, D., Shumansky, K., Wan, A., Lai, D., Mes-Masson, A-M., Aparicio, S., Shah, S. P., Engineered in-vitro cell line mixtures and robust evaluation of computational methods for clonal decomposition and longitudinal dynamics in cancer, Nature Scientific Reports 7(1), 13467. *Authors contributed equally to this work.

de Souza, C. P. E., Heckman, N. E. and Xu, F., (2017) Switching nonparametric regression models for multi-curve data, The Canadian Journal of Statistics, 45, 442-460. 

McPherson, A., Roth, A., Ha, G., Chauve, C., Steif, A., de Souza, C. P. E., Eirew, P., Bouchard-Côté, A., Aparicio, S., Sahinalp, S., and Shah, S., (2017) ReMixT: Clone Specific Genomic Structure Estimation in Cancer, Genome biology, 18(1), 140

Lenzi, A., de Souza, C. P. E., Dias, R., Garcia, N. L. and Heckman, N. E. (2017) Analysis of aggregated functional data from mixed populations with application to energy consumption, Environmetrics, 28(2)

Eirew, P., Steif, A., Jaswinder, K., Ha, G., Yap, D., Farahani, H., Gelmon, K., Chia, S., Mar, C., Wan, A., Laks, E., Biele, J., Shumansky, K., Rosner, J., McPherson, A., Nielsen, C., Roth, A., Lefebvre C., Bashashati, A., de Souza, C., Siu, C., Aniba, R., Brimhall, J., Oloumi, A., Osako, T., Bruna, A., Sandoval, J.,  Algara, T., Greenwood, W., Leung, K., Cheng, H., Xue, H., Wang, Y., Lin, D., Mungall, A., Moore, R., Zhao, Y., Lorette, J., Nguyen, L., Huntsman, D., Eaves, C. J., Hansen, C., Marra, M. A., Caldas, C., Shah, S. P., Aparicio, S. (2015)  Dynamics of genomic clones in breast cancer patient xenografts at single cell resolution, Nature 518, 422–426

De Souza, C. P. E. and Heckman, N. E. (2014) Switching nonparametric regression models, Journal of Nonparametric Statistics, 26(4), 617-637 (winner of the 2014 Journal of Nonparametric Statistics Best Student Paper Award). R package switchnpreg available.

De Souza, C. P. E. and Dias, R. (2010) Introdução à Análise de Dados Funcionais (Introduction to Functional Data Analysis). Monograph from the 19th National Symposium of Probability and Statistics (135 pages). Published by Associação Brasileira de Estatística (Brazilian Association of Statistics), São Paulo, Brazil.