Bledar Alex Konomi

Bledar Alex Konomi

Associate Professor, Statistics

French Hall


A&S Mathematical Sciences - 0025


PhD in Statistics, Texas A&M University College Station, 2011

BS, Athens University of Economics and Business Greece, 2005 (Statistics)

Positions and Work Experience

10-20-2011 -06-20-2014 Postdoctoral Research Assistant , Pacific Northwest National Laboratory, Richland, WA

Research and Practice Interests

My research area is in Bayesian statistics, computational methods of large spatial and computer simulation data sets ("big data"), and  uncertainty quantification. My primary applications have been in spatial and spatio-temporal  statistics, sequential design, computer model calibration and image analysis.

Research Support

Grant: #Sub #1650478 Investigators:Kang, Lei; Konomi, Bledar 05-01-2020 -12-31-2020 California Institute of Technology Jet Propulsion Laboratory (JPL) LARGE-SCALE MULTIVARIATE SPATIAL MODLEING FOR UNCERTIANTY QUANTIFICATION FOR AIRS MISSION Role:Collaborator $48,171.00 Awarded Level:Institution of Higher Education


Peer Reviewed Publications

Konomi, B. A., Hanandeh, A. A., Ma, P., Kang, E. L. (2019. ) Computationally Efficient Nonstationary Nearest Neighbor Gaussian Process Models Using Data-driven Techniques .Environmetrics, , e2571

Ma, P., Konomi, B. A., Kang, E. L. (2019. ) An Additive Approximate Gaussian Process for Large Spatio-Temporal Data .Environmetrics, , e2569 ,

Konomi, B. , Karagiannis, G., Lai, C. & Lin, G. (2017. ) Bayesian Treed Calibration: an application to carbon capture with AX sorbent.Journal of the American Statistical Association, , 112 (517 ) ,37-53

Karagiannis, G., Konomi, B., Lin, G., & Liang F. (2017. ) Parallel and Interacting Stochastic Approximation Annealing algorithms for global optimisation.Statistics and Computing, , 27 ( 4 ) ,927--945

Karagiannis, G., Konomi, B. A., and Lin, G (2019. ) On the Bayesian calibration of expensive computer models with input dependent parameters.Spatial Statistics, , 34 (December ) ,100258

Shi H., Kang E.L., Konomi B.A., Vemaganti K., Madireddy S. (2017. ) Uncertainty Quantification Using the Nearest Neighbor Gaussian Process. New Advances in Statistics and Data Science. ICSA Book Series in Statistics. Springer, Cham, ,

Konomi, B. A. and Lin, G. (2015. ) Low-Cost Multi-dimensional Gaussian Process with Application to Uncertainty Quantification .International Journal for Uncertainty Quantification, , 5 (4 ) ,375-392

Konomi, B. A. , Karagiannis, G., Lin, G. (2015. ) On the Bayesian Treed Multivariate Gaussian Process with Linear Model of Coregionalization .Journal of Statistical Planning and Inference, , 157 (3 ) ,1–15

Karagiannis, G. , Konomi, B. A., & Lin, G. (2015. ) A Bayesian mixed shrinkage prior procedure for spatial-stochastic basis selection and evaluation of gPC expansions: Applications to elliptic SPDEs .Journal of Computational Physics, , 284 (1 March ) ,528–546

Zhang, B., Konomi, B. A., Sang, H., Karagiannis, G., & Lin, G. (2015. ) Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions .Journal of Computational Physics, , 300 (November ) ,623–642

Konomi*, B. A., Sang, H. , Mallick, B. K (2014. ) Adaptive Bayesian nonstationary modeling for large spatial datasets using covariance approximations .Journal of Computational and Graphical Statistics, , 23 (3 ) ,802-829

Konomi, B, Karagiannis, G, Sarkar, A, Sun, X, Lin, G (2014. ) Bayesian Treed Multivariate Gaussian Process with Adaptive Design: Application to a Carbon Capture Unit .Technometrics , , 56 (2 ) ,145-158

Bilionis, I, Zabaras, N, Konomi, B, Lin, G (2013. ) Multi-output separable Gaussian process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification .Journal of Computational Physics, , 241 (1 ) , 212–239

Konomi,B., S. Dhavala, J. Huang, S. Kundu, D. Huitink, H. Liang, Y. Ding, and B. K. Mallick, (2013. ) Bayesian object segmentation and classification of gold nano-particles . Annals of Applied Statistics , , 7 (2 ) ,640-668

Konomi, B. A., and Karagiannis, G. (2020. ) Bayesian analysis of multifidelity computer models with local features and non-nested experimental designs: Application to the WRF model.Technometrics , ,

Pulong Ma, Anirban Mondal, Bledar A. Konomi, Jonathan Hobbs, Joon JinSong, & Emily L. Kang (2021. ) Computer Model Emulation with High-Dimensional Functional Output in Large-ScaleObserving System Uncertainty Experiments.Technometrics, ,

Other Publications

P Ramuhalli, G Lin, SL Crawford, B Konomi, BG Braatz (2014. ) Uncertainty Quantification Techniques for Sensor Calibration Monitoring in Nuclear Power Plants . Pacific Northwest National Laboratory

Student Advising

Si Cheng (Doctoral ) Advisor Status:In Progress

Seth Bennett (Doctoral ) Advisor Status:In Progress

Pulong Ma (Doctoral ) Co-Chair Status:Completed 06-01-2018

Ahmad A. Hanandeh (Doctoral ) Chair Status:Completed 08-2017

Courses Taught

-STAT-6021 MATH STATS I Level:Graduate

-STAT-3038 Probability & Statistics II Level:Undergraduate