Selected publications

Journal (refereed):

  1. Tomal, JH., Welch, WJ., and Zamar, RH. (2023). Robust ranking by ensembling of diverse models and assessment metrics. Journal of Statistical Computation and Simulation (Taylor & Francis). 1-26. https://doi.org/10.1080/00949655.2022.2093873
  2. Puliparambil, B.S., Tomal, JH., Yan, Y. (2022). A Novel Algorithm for Feature Selection Using Penalized Regression with Applications to Single-Cell RNA Sequencing Data (MDPI). 11, 1495. https://doi.org/10.3390/biology11101495
  3. Tomal, JH., Khan, JR., and Wahed, A. (2022). Weighted Bayesian Poisson Regression for The Number of Children Ever Born per Woman in Bangladesh. Journal of Statistical Theory and Applications (Springer). 1-27. https://doi.org/10.1007/s44199-022-00044-2
  4. Chowdhury, RI., and Tomal, JH. (2022). Risk prediction for repeated measures health outcomes: A divide and recombine framework. Informatics in Medicine Unlocked (Elsevier). 28: 100847. https://doi.org/10.1016/j.imu.2022.100847
  5. Atkins, M., Howarth, C., Russello, M., Tomal, JH., and Larsen, K. (2022). Evidence of intrapopulation differences in rattlesnake defensive behavior across neighboring habitats. Behavioral Ecology and Sociobiology (Springer). 76(3): 1-11. https://doi.org/10.1007/s00265-021-03100-6
  6. Tomal, JH., and Rahman, H. (2021). A Bayesian piecewise linear model for the detection of breakpoints in housing prices. METRON (Springer). 79(3): 361-381. https://doi.org/10.1007/s40300-021-00223-8
  7. Hsu, GG., Tomal, JH., and Welch, WJ. (2021). EPX: An R package for the ensemble of subsets of variables for highly unbalanced binary classification. Computers in Biology and Medicine (Elsevier). 136: 104760. https://doi.org/10.1016/j.compbiomed.2021.104760
  8. Khan, JR., Tomal, JH., and Raheem, E. (2021). Model and Variable Selection using Machine Learning Methods with Applications to Childhood Stunting in Bangladesh. Informatics for Health and Social Care (Taylor and Francis). 0: 1-18. https://doi.org/10.1080/17538157.2021.1904938
  9. Tomal, JH., Rahmati, S., Boroushaki, S., Jin, L., and Ahmed, E. (2021). The Impact of COVID-19 on Students’ Marks: A Bayesian Hierarchical Modeling Approach. METRON (Springer). 79: 57-91. https://doi.org/10.1007/s40300-021-00200-1
  10. Tomal, JH., and Ciborowski, JJH. (2020). Ecological Models for Estimating Breakpoints and Prediction Intervals. Ecology and Evolution (Wiley). 10:13500– 13517. https://doi.org/10.1002/ece3.6955
  11. Evans, M., and Tomal, JH. (2018). Measuring Statistical Evidence and Multiple Testing. FACETS. 3: 563-583. https://doi.org/10.1139/facets-2017-0121
  12. Tomal, JH., Welch, WJ., and Zamar, RH. (2017). Discussion of “Random projection Ensemble Classification” by T.I. Cannings and R.J. Samworth. Journal of the Royal Statistical Society: Series B. 79(4):1024-1025. https://doi.org/10.1111/rssb.12228
  13. Tomal, JH., Welch, WJ., and Zamar, RH. (2016). Exploiting Multiple Descriptor Sets in QSAR Studies. Journal of Chemical Information and Modeling. 56(3):501-509. https://doi.org/10.1021/acs.jcim.5b00663
  14. Tomal, JH., Welch, WJ., and Zamar, RH. (2015). Ensembling Classification Models Based on Phalanxes of Variables with Applications in Drug Discovery. The Annals of Applied Statistics, 9(1): 69-93. https://doi.org/10.1214/14-AOAS778

Conference (refereed):

  1. Kohli, N., Tomal, JH., Lin, W., and Yan Y. (Nov 18, 2024). PentaPen: Combining Penalized Models to Identify Important SNPs on Whole-genome Arabidopsis thaliana Data. ICBBT '24: Proceedings of the 2024 16th International Conference on Bioinformatics and Biomedical Technology . ICBBT 2024, Chongqing, China, 2024, pp. 9-16, doi: https://doi.org/10.1145/3674658.3674660
  2. Kohli, N., Tomal, JH., and Yan Y. (2023). Identification of Important SNPs using Bayesian Deep Learning on Whole-Genome Arabidopsis thaliana Data. IEEE International Conference on Bioinformatics and Biomedicine. BIBM 2023, Istanbul, Turkiye, 2023, pp. 328-332, doi: https://doi.org/10.1109/BIBM58861.2023.10385457
  3. Puliparambil, B.S., Tomal, JH., Yan, Y. (2022). Benchmarking Penalized Regression Methods in Machine Learning for Single Cell RNA Sequencing Data. In: Jin, L., Durand, D. (eds) Comparative Genomics. RECOMB-CG 2022. Lecture Notes in Computer Science, Vol: 13234. Springer. https://doi.org/10.1007/978-3-031-06220-9_17
  4. Lea, B., Shome, D., Waqar, O., and Tomal, JH. (2021). Sum rate maximization of D2D networks with energy constrained UAVs through deep unsupervised learning. 2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), pp. 453-459. https://doi.org/10.1109/UEMCON53757.2021.9666500
  5. Ciborowski, JJ., Johnson, LB., Tomal, JH., Fung, K., Bhagat, Y., and Zhang, J. (2009). The reference-degraded continuum–assessing biological condition relative to anthropogenic disturbance. NABS 57th Annual Meeting. Grand Rapids. https://nabs.confex.com/nabs/2009/techprogram/P3834.HTM

Other (non-refereed):

  1. Tomal, J., Rahman, H. (2021). Updated report on Kamloops's housing market. Technical report, Thompson Rivers University, Kamloops, British Columbia, Canada. https://faculty.tru.ca/jtomal/pages/Technical_report_Kamloops_housing.pdf
  2. Tomal, JH., Hsu, GG., Welch, WJ., and Wang, M. (2020). EPX: Ensemble of Phalanxes. R package version 1.0.4. https://cran.r-project.org/web/packages/EPX/index.html
  3. Tomal, JH., and Ciborowski, JJH. (2020). Datasets relating (i) A wetland fish multimetric index to variation in agricultural stress among Laurentian Great Lakes coastal wetlands, (ii) Cyanobacteria biomass to total phosphorus concentrations among Canadian lakes. Dryad, Dataset. https://doi.org/10.5061/dryad.g79cnp5nr
  4. Ciborowski, JJH., Landry, J., Wang, L., and Tomal, JH. (2020). Compiling and Assessing Environmental Stress Data for the Detroit River Area of Concern. Environment and Climate Change Canada
  5. Cai, Y., Cai, J., Chen, J., Golchi, S., Guan, M., Karim, ME., Liu, Y., Tomal, JH., Xiong, C., Zhai, Y., Lum, C., Welch, WJ., Zidek, JV. (2016). An Epirical Experiment to Assess the Relationship Between the Tensile and Bending Strengths of Lumber. Technical Report, Department of Statistics, The University of British Columbia, Vancouver, BC, Canada. https://www.stat.ubc.ca/Research/TechReports/tr/276.pdf