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Pierre
Miasnikof

Assistant Professor

Department of Operations and Decision Systems
FSA ULaval
Pavillon Palasis-Prince
Local 2519

Education

  • Doctor of Philosophy, Engineering Informatics (Ph. D.), University of Toronto
  • Master of Science, Mechanical & Industrial Engineering. (optimization) (M. Sc.), University of Toronto
  • Bachelor, Economics (B. Sc.), Université de Montréal

Publications

Articles

  • Miasnikof, P., Bagherbeik, M., & Sheikholeslami, A. (2023). Graph clustering with Boltzmann machines. Discrete Applied Mathematics, 343(3), 208-223. DOI : 10.1016/j.dam.2023.10.012
  • Miasnikof, P. (2023). Distance correlation market graph: The case of S&P500 stocks. Mathematics, 11(18), 3832. DOI : 10.3390/math11183832
  • Miasnikof, P., Shestopaloff, A. Y., & Raigorodskii, A. (2023). Statistical power, accuracy, reproducibility and robustness of a graph clusterability test. International Journal of Data Science and Analytics, 15(4), 379-390. DOI : 10.1007/s41060-023-00389-6
  • Miasnikof, P., Shestopaloff, A. Y., Pitsoulis, L., & Ponomarenko, A. (2022). An empirical comparison of connectivity-based distances on a graph and their computational scalability. Journal of Complex Networks, 10(1), cnac003. DOI : 10.1093/comnet/cnac003
  • Pazinski Hong, S. W., Miasnikof, P., Kwon, R., & Lawryshyn, Y. (2021). Market graph clustering via QUBO and digital annealing. Journal of Risk and Financial Management, 14(1), 34. DOI : 10.3390/jrfm14010034
  • Miasnikof, P., Shestopaloff, A. Y., Bonner, A. J., Lawryshyn, Y., & Pardalos, P. (2020). A density-based statistical analysis of graph clustering algorithm performance. Journal of Complex Networks, 8(3), cnaa012. DOI : 10.1093/comnet/cnaa012
  • Miasnikof, P., Giannakeas, V., Gomes, M., Aleksandrowicz, L., Alam, D. S., Tollman, S., Samarikhalaj, A., & Jha, P. (2015). Naive Bayes classifiers for verbal autopsies: Comparison to physician-based classification for 21,000 child and adult deaths. BMC Medicine, 13(1), 286. DOI : 10.1186/s12916-015-0521-2
  • Desai, N., Aleksandrowicz, L., Miasnikof, P., Lu, Y., Leitao, J., Byass, P., Tollman, S., Mee, P., Alam, D. S., Rathi, S. K. R., Singh, A., Kumar, R., Ram, F., & Jha, P. (2014). Performance of four computer-coded verbal autopsy methods for cause of death assignment compared with physician coding on 24,000 deaths in low- and middle-income countries. BMC Medicine, 12(1), 20. DOI : 10.1186/1741-7015-12-20
  • Aleksandrowicz, L., Malhotra, V., Dikshit, R., Gupta, P. C., Kumar, R., Sheth, J. K., Rathi, S. K., Suraweera, W., Miasnikof, P., Jotkar, R. M., Sinha, D. N., Awasthi, S., Bhatia, P., & Jha, P. (2014). Performance criteria for verbal autopsy-based systems to estimate national causes of death: Development and application to the Indian million death study. BMC Medicine, 12(1), 21. DOI : 10.1186/1741-7015-12-21
  • Leitao, J., Desai, N., Aleksandrowicz, L., Byass, P., Miasnikof, P., Tollman, S., Alam, D. S., Lu, Y., Rathi, S. K., Singh, A., Suraweera, W., Ram, F., & Jha, P. (2014). Comparison of physician-certified verbal autopsy with computer-coded verbal autopsy for cause of death assignment in hospitalized patients in low- and middle-income countries: Systematic review. BMC Medicine, 12(1), 22. DOI : 10.1186/1741-7015-12-22

Chapters in Collective Works

  • Miasnikof, P., Shestopaloff, A. Y., Bravo, C., & Lawryshyn, Y. (2024). Empirical study of graph spectra and their limitations. Complex networks and their applications XII (pp. 295-307). Springer. doi : 10.1007/978-3-031-53468-3_25.
  • Miasnikof, P., Shestopaloff, A. Y., Bravo, C., & Lawryshyn, Y. (2023). Statistical network similarity. Complex Networks and Their Applications XI (pp. 325-336). Springer. doi : 10.1007/978-3-031-21131-7_25.
  • Miasnikof, P., Shestopaloff, A. Y., Pitsoulis, L., Ponomarenko, A., & Lawryshyn, Y. (2021). Distances on a graph. Complex Networks & Their Applications IX (pp. 189-199). Springer. doi : 10.1007/978-3-030-65347-7_16.
  • Miasnikof, P., Pitsoulis, L., Bonner, A. J., Lawryshyn, Y., & Pardalos, P. (2020). Graph clustering via intra-cluster density maximization. Network Algorithms, Data Mining, and Applications (pp. 37-48). Springer. doi : 10.1007/978-3-030-37157-9_3.
  • Miasnikof, P., Prokhorenkova, L. O., Shestopaloff, A. Y., & Raigorodskii, A. (2020). A statistical test of heterogeneous subgraph densities to assess clusterability. Learning and Intelligent Optimization (pp. 17-29). Springer. doi : 10.1007/978-3-030-38629-0_2.
  • Miasnikof, P., Shestopaloff, A. Y., Bonner, A. J., & Lawryshyn, Y. (2018). A statistical performance analysis of graph clustering algorithms. Algorithms and Models for the Web Graph (pp. 170-184). Springer. doi : 10.1007/978-3-319-92871-5_11.

Communications in a Conference with Proceedings

  • Miasnikof, P., Prokhorenkova, L. O., Shestopaloff, A. Y., & Raigorodskii, A. (2019). A statistical test of heterogeneous subgraph densities to assess clusterability. 13th LION Learning and Intelligent OptimizatioN Conference, Chania, Crete, Greece.
  • Miasnikof, P., Pitsoulis, L., Bonner, A. J., Lawryshyn, Y., & Pardalos, P. (2018). Graph clustering via intra-cluster density maximization. The 8th International Conference on Network Analysis, Moscou, Russia.

Communications in a Conference Without Proceedings

  • Miasnikof, P. (2023). Empirical study of graph spectra and their limitations. Complex Networks 2023, Menton, France.
  • Miasnikof, P. (2022). Statistical network similarity. Complex networks and their applications, Palerme, Italy.
  • Miasnikof, P. (2021). Clustering with a Boltzmann Machine. World Congress on Global Optimization 2021, Athènes, Greece.
  • Miasnikof, P. (2021). Clustering with a permutational boltzmann machine. CORS 2021, En ligne, Canada.
  • Miasnikof, P. (2020). Distances on a graph. Complex Networks 2020, Madrid, Spain.
  • Miasnikof, P. (2020). Graphs in Metric Space. The 10th International Conference on Network Analysis, Laboratory of Algorithms and Technologies for Networks Analysis, En ligne, Canada.
  • Miasnikof, P. (2020). Graphs, unsupervised learning, complex networks and pandemic modeling. MyTrace Workshop, Canada.
  • Miasnikof, P. (2019). A statistical test of heterogeneous subgraph densities to assess clusterability. 13th LION Learning and Intelligent Optimization Conference, Chania, Crète, Greece.
  • Miasnikof, P. (2019). Graph clustering via digital annealer. The 9th International Conference on Network Analysis, Moscou, Russia.
  • Miasnikof, P. (2018). Metaheuristics for large-scale graph clustering. The 8th International Conference on Network Analysis, Moscou, Russia.
  • Miasnikof, P. (2018). A statistical performance analysis of graph clustering algorithms. 15th Workshop on Algorithms and Models for the Web Graph, Moscou, Russia.
  • Miasnikof, P. (2017). Graph clustering performance. Yandex Research, Moscou, Russia.

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