Oleg Sysoev
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My current research is focused on development of novel statistical machine learning models for different applications, primarily in personalized medicine, public health and in telecommunications. The methods proposed in my publications are based on decision trees, kernel models, neural networks and statistical uncertainty evaluation methods such as bootstrap and jackknife. I have been also working on creating models for large-scale data, in particular monotonic regression models for large and multivariate data.

My journal publications:

  • (2022) Li X., Lee EJ, Lilja S., Loscalzo J., Schäfer S., Smelik M., Strobl M.R., Sysoev O., Wang H., Zhang H., Zhao Y., Gawel D.R., Bohle B., Benson. A dynamic single cell-based framework for digital twins to prioritize disease genes and drug targets. Genome Medicine 14:48
  • (2022) Svahn C., Sysoev. O. Selective Imputation of Covariates in High Dimensional Censored Data. Accepted to Journal of Computational and Graphical Statistics. DOI:10.1080/10618600.2022.2035233
  • (2021) Pérez W., Selling K.E, Blandón E.Z, Peña R., Contreras M, Persson LA, Sysoev O., Källestål C.  Trends and factors related to adolescent pregnancies: an incidence trend and conditional inference trees analysis of northern Nicaragua demographic surveillance data. BMC Pregnancy Childbirth  21, 749
  • (2020) Lee EJ, Gawel D, Lilja S, Li X, Schäfer S, Sysoev O, Zhang H and Benson M. . Analysis of expression profiling data suggests explanation for difficulties in finding biomarkers for nasal polyps. Rhinology 58(4) pp. 360-367.
  • (2020) Björnsson B, Borrebaeck C, Elander N, Gasslander T, Gawel DR, Gustafsson M, Jörnsten R, Lee EJ, Li X, Lilja S, Martínez-Enguita D, Matussek A, Sandström P, Schäfer S, Stenmarker M, Sun XF, Sysoev O, Zhang H, Benson M. Digital twins to personalize medicine.  Genome Med 12, 4, doi: 10.1186/s13073-019-0701-3
  • (2020) Källestål C., Blandón E.Z., Peña R., Peréz W., Contreras M., Persson L.Å., Sysoev O. Selling, K.E.: Assessing the Multiple Dimensions of Poverty. Data Mining Approaches to the 2004–14 Health and Demographic Surveillance System in Cuatro Santos, Nicaragua. Frontiers in Public Health vol 7, pp 409. doi: 10.1186/s12939-019-1054-7
  • (2019) Källestål C., Blandón E.Z., Peña R., Peréz W., Contreras M., Persson L.Å., Sysoev O. Selling, K.E.: Predicting poverty. Data mining approaches to the health and demographic surveillance system in Cuatro Santos, Nicaragua. International Journal for Equity in Health vol 18, no 165. doi: 10.3389/fpubh.2019.00409
  • (2019) Svefors P., Sysoev O., Ekström E.C., Person L.Å., El Arifeen S., Naved R., Rahman A., Islam Khan A., Ekholm Selling K.: Relative importance of prenatal and postnatal determinants of stunting: data mining approaches to the MINIMat cohort, Bangladesh. BMJ Open vol 9:e025154. doi: 10.1136/bmjopen-2018-025154
  • (2019) Sysoev. O, Bartoszek K., Ekstrom EC and Ekholm Selling K. PSICA: decision trees for probabilistic subgroup identification with categorical treatments. Statistics in Medicine, pp. 1– 17. doi : 10.1002/sim.8308
  • (2018) Sysoev, O., Burdakov, O. A smoothed monotonic regression via l2 regularization. Knowledge and Information Systems, 1-22.
  • (2017) Burdakov, O., Sysoev, O. A Dual Active-Set Algorithm for Regularized Monotonic Regression. Journal of Optimization Theory and Applications 172.3: 929-949.
  • (2016) Kalish, M.L, Dunn J.C., Burdakov O. and Sysoev O.: A statistical test of the equality of latent orders Journal of mathematical psychology, vol 70, pp 1-11.
  • (2015) Sysoev, O., Grimvall, A., and Burdakov, O..: Bootstrap confidence intervals for large-scale multivariate monotonic regression problems. Statistics-Simulation and Computation, pp 1-16.
  • (2013) Sysoev, O., Grimvall, A., and Burdakov, O.: Bootstrap estimation of the variance of the error term in monotonic regression models. Journal of Statistical Computation and Simulation 83.4 : pp 627-640.
  • (2011) Sysoev, O., Burdakov, O., Grimvall, A.: A Segmentation-Based Algorithm for Large-Scale Monotonic Regression Problems. Computational Statistics and Data Analysis 55, pp. 2463-2476
  • (2006) Burdakov, A. Grimvall and O. Sysoev. Data preordering in generalized PAV algorithm for monotonic regression. Journal of Computational Mathematics. 24, No. 6, pp. 771-790.
  • (2006) Burdakov O. , Sysoev O. ,Grimvall A. and Hussian M. An O(n2) algorithm for isotonic regression. In: G. Di Pillo and M. Roma (Eds) Large-Scale Nonlinear Optimization. Series: Nonconvex Optimization and Its Applications, Springer-Verlag, 83, pp. 25-33.
  • (2005) Hussian M. ,Grimvall A. ,Burdakov O. and Sysoev O. Monotonic regression for the detection of temporal trends in environmental quality data. MATCH Commun. Math. Comput. Chem. 54, pp. 535-550.

My conference publications:

  • (2022) Svahn, C., Sysoev. O,: CCVAE: A variational autoencoder for handling sensored covariates. Accepted to ICMLA 2022.
  • (2021) Sysoev O., Gawel D., Lilja S., Schäfer S., Benson M. Cell type identification for single cell RNA data by bulk data reference projection. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 742-746, doi: 10.1109/BIBM52615.2021.9669148.
  • (2019) Svahn, C., Sysoev, O., Cirkic M., Gunnarsson F. and Berglund J.: Inter-frequency radio signal quality prediction for handover, evaluated in 3GPP LTE. 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), Kuala Lumpur, Malaysia, pp. 1-5. doi: 10.1109/VTCSpring.2019.8746369
  • (2013) Sysoev, O.: Estimating binary monotonic regression models and their uncertainty by incorporating kernel smoothers. Complex Data Modelling and Computationally Intensive Statistical Methods for Estimation and Prediction conference.
  • (2009) O. Burdakov, A. Grimvall and O. Sysoev. Generalized PAV algorithm with block refinement for partially ordered monotonic regression. In: A. Feelders and R. Potharst (Eds.) Proceedings of the Workshop on Learning Monotone Models from Data at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pp. 23-37.
  • (2004) O. Burdakov, O. Sysoev, A. Grimvall and M. Hussian. An algorithm for isotonic regression problems. In: The Proceedings of the 4th European Congress of Computational Methods in Applied Science and Engineering `ECCOMAS 2004'.
  •  (2004) M. Hussian, A. Grimvall, O. Burdakov and O. Sysoev. Monotonic regression for trend
    assessment of environmental quality data.     In: The Proceedings of the 4th European Congress of
    Computational Methods in Applied Science and Engineering `ECCOMAS 2004'

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Last updated: 2022-11-25