Publications
Published papers in journals ...
- Cheng, S., Konomi, B. A., Karagiannis, G.,
& Kang, E. L. (2024). Recursive nearest neighbor co‐kriging
models for big multi‐fidelity spatial data sets. Environmetrics,
e2844. Environmetrics
- Ma, P., Karagiannis, G., Konomi, B.A., Asher, T.G., Toro, G.R.
& Cox, A.T. (2022) Multifidelity computer model emulation with
high-dimensional output: An application to storm surge. Journal of
the Royal Statistical Society: Series C, 1–23
- Chang, W., Konomi, B. A., Karagiannis, G., Guan, Y., &
Haran, M. (2022). Ice Model Calibration Using Semi-continuous
Spatial Data. Annals of Applied Statistics.
- Karagiannis, G., Hou, Z., Huang, M., & Lin, G. (2022).
Inverse modeling of hydrologic parameters in CLM4 via generalized
polynomial chaos in the Bayesian framework. Computation, 10(5),
72.
- Cheng, S., Konomi, B. A., Matthews, J. L., Karagiannis, G.,
& Kang, E. L. (2021). Hierarchical Bayesian nearest neighbor
co-kriging Gaussian process models; an application to
intersatellite calibration. Spatial Statistics, 100516.
- Konomi, B. A., & Karagiannis, G. (2020). Bayesian analysis
of multifidelity computer models with local features and
non-nested experimental designs: Application to the WRF model. Technometrics.,
1-31.
- Karagiannis, G., Hao, W., & Lin, G. (2020) Calibrations and
validations of biological models with an application on the renal
fibrosis. International Journal for Numerical Methods in
Biomedical Engineering, e3329.
- Karagiannis, G., Konomi, B. A., & Lin, G. (2019). On the
Bayesian calibration of expensive computer models with input
dependent parameters, Spatial Statistics
- Alamaniotis, M., & Karagiannis, G. (2019). Application of
fuzzy multiplexing of learning Gaussian processes for the interval
forecasting of wind speed. IET Renewable Power Generation. –
Special Issue from Medpower 2018.
- Karagiannis, G., Konomi, B. A., Lin, G., & Liang, F. (2017).
Parallel and interacting stochastic approximation annealing
algorithms for global optimisation. Statistics and Computing,
27(4):927–945.
- Konomi, B. A., Karagiannis, G., Lai, K., & 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., & Lin, G. (2017). On the Bayesian
calibration of computer model mixtures through experimental data,
and the design of predictive models. Journal of Computational
Physics, 342:139 - 160.
- Alamaniotis, M., & Karagiannis, G. (2017). Integration of
Gaussian Processes and Particle Swarm Optimization for Very-Short
Term Wind Speed Forecasting in Smart Power. International Journal
of Monitoring and Surveillance Technologies Research (IJMSTR),
5(3), 1-14.
- 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, 284:528
- 546.
- 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, 157-158:1 - 15.
- 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, 300:623 - 642.
- Karagiannis, G. , & Lin, G. (2014). Selection of polynomial
chaos bases via Bayesian model uncertainty methods with
applications to sparse approximation of PDEs with stochastic
inputs. Journal of Computational Physics, 259:114 - 134.
- Konomi, B. A., 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.
- Karagiannis, G., & Andrieu, C. (2013). Annealed importance
sampling reversible jump MCMC algorithms. Journal of
Computational and Graphical Statistics, 22(3):623-648.
Published papers in conferences
...
- Deng, W., Feng, Q., Karagiannis, G., Lin, G., & Liang, F.
(2021). Accelerating Convergence of Replica Exchange Stochastic
Gradient MCMC via Variance Reduction. International Conference on
Learning Representations (ICLR'21).
- Alamaniotis, M., Martinez-Molina, A., & Karagiannis, G.
(2021, June). Data Driven Update of Load Forecasts in Smart Power
Systems using Fuzzy Fusion of Learning GPs. In 2021 IEEE Madrid
PowerTech (pp. 1-6). IEEE.
- Alamaniotis, M., & Karagiannis, G. (2019, September).
Elm-fuzzy method for automated decision-making in price directed
electricity markets. In 2019 16th International Conference on the
European Energy Market (EEM) (pp. 1-5). IEEE.
- Alamaniotis, M., & Karagiannis, G. (2019, June). Minute
Ahead Wind Speed Forecasting Using a Gaussian Process and Fuzzy
Assimilation. In 2019 IEEE Milan PowerTech (pp. 1-6). IEEE.
- Alamaniotis, M., & Karagiannis, G. (2018, November).
Learning uncertainty of wind speed forecasting using a fuzzy
multiplexer of Gaussian processes. In Mediterranean Conference on
Power Generation, Transmission, Distribution and Energy Conversion
(MEDPOWER 2018) (pp. 1-6). IET.
- Alamaniotis, M. & Karagiannis, G. (2018), Genetic Driven
Multi-Relevance Vector Regression Forecasting of Hourly Wind Speed
in Smart Power Systems, The Ninth Annual IEEE PES Conference on
Innovative Smart Grid Technology North America. Washington, DC
- Nasiakou, A., Alamaniotis, M., Tsoukalas, L.H. &
Karagiannis, G. (2017), A Three-Stage Scheme for Consumers'
Partitioning Using Hierarchical Clustering Algorithm, 8th
International Conference on Information, Systems and Applications
(IISA). Larnaca, Cyprus, 6.
Book chapters ...
- Alamaniotis, M., & Karagiannis, G. (2023). Toward Smart
Energy Systems: The Case of Relevance Vector Regression Models in
Hourly Solar Power Forecasting. In Fusion of Machine Learning
Paradigms: Theory and Applications (pp. 119-127). Cham: Springer
International Publishing.
- Karagiannis G.P. (2022) Introduction to Bayesian Statistical
Inference. In: Aslett L.J.M., Coolen F.P.A., De Bock J. (eds)
Uncertainty in Engineering. SpringerBriefs in Statistics.
Springer, Cham.
Other published research outputs
...
- Qiu, T., Karagiannis, G., & Lin, G. (August 4, 2016). Model
Selection Using Gaussian Mixture Models and Parallel Computing,
The Summer Undergraduate Research Fellowship (SURF) Symposium,
Paper 142. [Link]
- Karagiannis, G. (2011). AISRJMCMC-Annealed Importance Sampling
within Reversible Jump Markov Chain Monte Carlo algorithm: a
pseudo-marginal reversible jump MCMC algorithm (Doctoral
dissertation, University of Bristol). [Link]
Editorial outputs ...
- Einbeck J., Drikvandi R., Karagiannis, G., Perrakis, K. (2024, July). Proceedings of the 38th International Workshop on Statistical Modelling. Presented at 38th International Workshop on Statistical Modelling (IWSM), Durham, UK (ISBN: 9780907552444). [Link]
Unpublished research outputs ...
- Karagiannis, G., Andrieu, C. (2009, 2016). Drawing samples from
inverse Wishart distributions conditioning on the 1st block
diagonal sub-matrix; with an application to variable selection on
a GLMM model with nested random effects, GitHub repository
manuscript, [Link]
Presentations
in scientific conferences / meetings ...
- Seminar talk in Hartree Centre, Warrington, UK
2024
- SIAM Conference on Uncertainty Quantification (UQ22), Atlanta,
GA / USA
2022
- UC Mathematics Department Colloquium, University of Cincinnati,
OH / USA
2020
- Departmental seminar, Department of Electrical and Computer
Engineering, UTSA, TX/USA
2020
- Statistics seminar, Department of statistics, AUEB, Greece
2019
- SAMSI program in Model Uncertainty: Mathematical and
Statistical, SAMSI, NC / USA
2018
- International Society for Bayesian Analysis meeting (ISBA2018),
Edinburgh, UK
2018
- SIAM Conference on Uncertainty Quantification (UQ18), Garden
Grove, CA / USA
2018
- Workshop on the Current Trends and Challenges in Data Science
and Uncertainty Quantification, Purdue University, IN / USA
2018
- ACMS Department Colloquium, University of Notre Dame, IN / USA
2016
- ASA Joint Statistical Meetings, Seattle, WA / USA
2015
- IdeaLab 2015, ICERM program, Brown University, RI / USA
2015
- 22nd ASA/IMS 2015 Spring Research Conference (SRC), OH / USA
2015
- UC Mathematics Department Colloquium, University of Cincinnati,
OH / USA
2015
- PNNL Post-doc Symposium, Richland, WA / USA
2014
- CRiSM model uncertainty workshop, University of Warwick, UK
2010
- Greek Stochastics a’ Monte Carlo: Probability and Methods,
Lefkada, Greece
2009
- Research students conference in probability and statistics,
University of Lancaster, UK
2009
- Research students conference in probability and statistics,
University of Nottingham, UK
2008