Dionissios T. Hristopulos Professor, Head of the Geostatistics Research Unit (GRU) Office: Room M3.206 |
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Research
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Research ActivitiesMy research focuses on the following directions: (1) The development of new geostatistical methods and their applications in mineral resources exploration, petroleum reservoir simulation, environmental monitoring, and GIS mapping functions. (2) The application of geostatistical and statistical physics techniques in stochastic hydrology. (3) The investigation of the impact of heterogeneity on the mechanical properties of porous materials such as advanced ceramics. (4) The investigation of the probability laws of earthquake return times as well as applications of geostatistics to the analysis of correlations between seismic events on different faults. |
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In a nutshell, Geostatistics aims to analyze the spatial structure of natural processes based on scattered data and to use the information for the purposes of estimation, interpolation and simulation at locations (or times) that are not accessible for measurement.
More specifically, I am currently interested in the following topics:
My efforts focus on modelling the effects of spatial variability in porous media at various scales, and especially in the calculation of coarse-grained parameters of transport properties such as fluid permeability and macro-dispersivity.
Another interest is the space-time modelling of the water table depth using geostatistical approaches.
My specific interests include the following topics:
This work was carried out in collaboration with the Laboratory of Ceramics and Glass Technology, and it was funded by the European project "Activation".
The research continues in collaboration with the laboratory of Physical Metallurgy of the National Technical University of Athens.My research in ceramics focuses on the following:
My work focuses on the probability laws of earthquake return times and applications of geostatistics to the analysis of correlations between seismic events on different faults of the same system.
This work is carried out in collaboration with the post-doctoral fellow Vasiliki Mouslopoulou and is funded by the European Commission FP7 program. For more information check the website of the project "Bridgseismtime".
Funding for research activities is provided by both national programs (Environment-Pythagoras II) and EU projects (Activation - STREP, Marie Curie Transfer of Knowledge fellowship).
My recent research has been supported by the following grants:
The Marie Curie Transfer Of Knowledge Grant SPATSTAT (2005-2008) for the development of Spartan Spatial Random Fields. This was selected by the European Commission as a Marie Curie success story and highlighted in the special edition "Marie Curie Actions: Inspiring Researchers", European Commission, Luxembourg: Publications Office of the European Union, 2010 ISBN 978-92-79-14328-1.
The multi-partner European Specific Targeted Research Project (STREP) Interoperability and Mapping INTAMAP (2006-2009). The TUC efforts focused on the development of spatial anisotropy detection methods for use in Bayesian interpolation frameworks used by INTAMAP.
The code (in R) developed by TUC and its partners is available for download through the project web site.
Introduction to Geostatistics (6th semester)
The course reviews basic principles of the theory of probability and statistics and then introduces the main concepts of spatial analysis.
Electrical Circuits (4th semester)
This course focuses on methods for solving linear electrical circuits, in both steady-state and transient conditions. I taught this course from 2003 till 2005.
Applications of Geostatistics (7th semester)
This course introduces the concept of random fields, the variogram function, kriging methods for interpolation and reserves estimation and other applications.
The course involves computer lab sessions that introduce the use of MATLAB in geostatistical calculations.
Data analysis / Geostatistics (graduate courses)
These courses alternate every year. They focus on the main concepts and applications of spectral analysis, regression methods, random field theory, simulation and geostatistics in relation to the analysis and processing of various "signals" with temporal or spatial variability.
The courses are complemented with computer lab sessions for hands-on practice of MATLAB data-processing functions.
Some introductory notes for MATLAB are here (in Greek).
The following is a list of researchers and students who have recently collaborated or are still collaborating with the Geostatistics Research Unit at TUC.
Professor Sujit Kumar Ghosh, from the Department of Statistics at the North Carolina State University (USA) has recently started a collaboration with TUC as a Marie-Curie fellow, to conduct research on the interface between Spartan Spatial Random Fields and Bayesian Statistics.
Dr. Samuel Elogne (currently in France) is a Marie-Curie fellow who conducted his post-doctoral studies on the development of Spartan Spatial Random Fields.
Dr. Milan Zukovic (currently an Associate Professor in Slovakia) is a Marie-Curie fellow who worked on the extension of Spartan Spatial Random Fields to data that follow non-Gaussian distributions using statistical physics models.
Dr. Ersi Chorti (currently at Middlesex University, London) is a post-doctoral researcher who focused on the development of non-parametric methods for the detection of spatial anisotropy from scattered data.
Dr. Aris Moustakas (currently at the University of Leeds) worked as a post-doctoral researcher on the application of geostatistical methods to problems in plant ecology.
Dr. Aliki Muradova is a researcher who developed a mathematical model for the formation and decomposition of gas hydrates below the seafloor.
Mr. Manolis Petrakis is a Master's student working on the development of mathematical expressions for characterizing the anisotropy of spatially scattered data.
Mr. Manos Varouchakis is a Ph.D candidate working on the monitoring of groundwater level in the Messara valley of Crete.
Mr. Andreas Pavlidis is a Master's student focusing on the application of geostatistical methods to the estimation of lignite reserves and quality variations from mines in West Macedonia (Greece).
Mr. Spyros Blanas (currently at the University of Wisconsin at Madison) as an undergraduate student worked on on the computational implementation of a grain growth model used with potential applications in sintering of ceramic materials.
Mr. Ioannis Kardaras as an undergraduate student conducted simulations of a grain growth and coalescence model.
Ms. Melina Demertzi (currently at the University of Southern California) as an undergraduate student developed a database of mechanical properties for ceramic materials and determined model coefficients for a new structure-property model.
Pulp and Paper Research Institute of
Canada
570 Boulevard St. Jean
Pointe-Claire, Quebec H9R 3J9
CANADA
At PAPRICAN, I was a member of the Product Performance Program. I specialized on statistical models of paper structure and the fracture mechanics of heterogeneous fibre materials.
The goal of my work was to identify physical parameters that control the quality of paper products. For example, paper breaks have a significant economic impact on the operation of pressrooms and paper machines. A better understanding of the fracture process in paper can lead to practices for minimizing the occurrence of breaks.
Department of Environmental Sciences and Engineering
University of North Carolina
at Chapel Hill
Chapel Hill, NC 27599-7400
At Chapel Hill, I was a member of the Center
for the Advanced Study of the Environment (CASE).
I collaborated with George
Christakos, Marc
Serre, and Casey
Miller. I also benefited from informal discussions with Markus
Hilpert.
My research at CASE focused on applications of statistical physics and field theory in environmental processes and heterogeneous porous media
Atmospheric and subsurface environmental processes are characterized by spatial and temporal variability that can be modeled mathematically by means of random fields.
Similarly, porous media (natural and technological), have heterogeneities at various physical scales, which influence their macroscopic (large-scale) behavior. More specifically:
My dissertation was in the field of Condensed Matter Physics.
My research focused on a specific model for the materials called high temperature
superconductors. These materials are ceramic compounds that conduct electrical
current with zero resistance at relatively high temperatures (above the liquefaction
temperature of nitrogen). My dissertation investigated the electronic states
of these materials in their normal state (i.e., at temperatures above the superconducting
threshold) using Monte Carlo simulations.
My advisors were Phil W. Anderson, and Sriram Shastry. Learning from and working with physicists like Phil Anderson was an invaluable part of the Princeton experience.
At Princeton I worked in the biophysics laboratory (Summer 1985) directed by Sol Gruner. My research focused on the X-ray analysis of biolipid structures. I had valuable advice and enjoyed discussions with Erramilli Shyamsunder.
I served as teaching assistant for Physics 101-102 (Fall 1986-Spring 1988). This was an introductory physics course in mechanics and electromagnetism for engineers. I conducted three-hour lab sessions twice every week.
During the next two years (Fall 1998-Spring 2000), I worked as teaching assistant for Physics 111, (also called Physics for Poets) a course for non-science majors taught at the time by Bob Austin.
The Physics department required completing an experimental project before starting the dissertation research. I worked with the solid-state physics group led by Russ Gianetta, and constructed an electromagnetic graphite fiber balance capable of measuring very small changes in mass (a few atomic layers of condensed gas) by changes in the fiber's oscillation frequency.
This project required good knowledge of experimental electronics, which I largely owe to the excellent graduate electronics course taught by Sol Gruner, and the invaluable practical advice of Bart Gibbs.
My diploma thesis focused on measuring the electro-optic coefficients of semiconductor crystals used in fiber optic communications. My advisor was Alexandros Serafetinides, a member of the Laser Group in the Physics Department.
Journal of Stochastic Environmental Research and Risk Assessment, Springer-Verlag .
G. Christakos and D.T. Hristopulos, Spatiotemporal Environmental Health Modeling, Kluwer Academic Publishers, Boston (1998).
I. Spiliopoulos, D. T. Hristopulos, E. Petrakis and A. Chorti (2011).
A Multigrid Method for the Estimation of Geometric Anisotropy in Environmental Data from Sensor Networks, Computers and Geosciences, doi
Dubois, G., Cornford, D., Hristopulos, D., Pebesma, E., Pilz, J., (2011).
Introduction to this special issue on geoinformatics for environmental surveillance,
Computers and Geosciences, doi
D. T. Hristopulos and M. Zukovic (2011).
Relationships between correlation lengths and integral scales for covariance models with more than two parameters, Stochastic Environmental Research and Risk Assessment,in press, doi
M. Zukovic and D. T. Hristopulos (2009a).
Classification of missing values in spatial data using spin models, Physical Review E, 80(1), 011116 (2009). doi
D. T. Hristopulos and S. N. Elogne (2009b).
Computationally efficient spatial interpolators based on Spartan spatial random fields, IEEE Transactions on Signal Processing, 57(9), 3475-3487.
M. Zukovic and D. T. Hristopulos (2009c).
The method of normalized correlations: a fast parameter estimation method for random processes and isotropic random fields that focuses on short-range dependence, Technometrics, 15(2), 173-185. doi
M. Zukovic and D.T. Hristopulos (2009).
Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data, Journal of Statistical Mechanics: Theory and Experiment, P02023, doi
M. Zukovic and D.T. Hristopulos (2008).
Environmental Time Series Interpolation Based on Spartan Random Processes, Atmospheric Environment, 42(33), 7669-7678.
A. Chorti and D.T. Hristopulos (2008).
Non-parametric Identification of Anisotropic
(Elliptic) Correlations in Spatially Distributed Data Sets, IEEE Transactions on Signal Processing, 56(10), 4738-4751.
S. Elogne, D.T. Hristopulos and E. Varouchakis (2008).
An application of Spartan spatial random fields in environmental mapping: focus on automatic mapping
capabilities,
Stochastic Environmental Research and Risk Assessment, 52(5), 633 - 646.
A. Moustakas and D.T. Hristopulos (2008).
Estimating tree abundance from remotely sensed imagery in semi-arid and arid environments: bringing
small trees to the light, Stochastic Environmental Research and Risk Assessment, in press.
M. Zukovic and D.T. Hristopulos (2008).
Spartan random processes in time series modeling , Physica A-Statistical
Mechanics And Its Applications, 387(15),
3995-4001. Preprint.
D.T. Hristopulos and M. Demertzi (2008).
A semi-analytical equation for the Young's modulus of isotropic ceramic materials, Journal of the European
Ceramic Society, 28(6), 1111-1120.
D.T. Hristopulos and S. Elogne (2007).
Analytic properties and covariance functions for a new class of generalized Gibbs random fields, IEEE
Transactions on Information Theory, 53(12), 4667-4679.
A. Moustakas, A. Chorti and D.T. Hristopulos (2007\oint).
Geostatistical analysis of tree size distributions in the Southern
Kalahari, obtained from remotely sensed data, Proceedings of SPIE - The International Society for
Optical Engineering, Volume 6742, 2007, Article number 67420G.
D.T. Hristopulos, (2006).
Identification of Spatial Anisotropy by means of the Govariance Tensor Identity,
In: Automatic
Mapping Algorithms for Routine and Emergency Monitoring Data: Spatial Interpolation
Comparison 2004, (edited by G. Dubois), Office for Official
Publications of the European Communities, Luxembourg, ISBN 92-894-9400-X,
pp. 103-124. Online at: http://www.ai-geostats.org/events/sic2004.htm.
D.T. Hristopulos, L. Leonidakis and A. Tsetsekou, (2006).
A Discrete Nonlinear Mass Transfer Equation with Applications in Solid-State
Sintering of Ceramic Materials, European
Physical Journal B - Condensed Matter Physics, 50(1-2),
83-87. Preprint.
D.T. Hristopulos, (2006).
Spartan Spatial Random Field Models Inspired from Statistical Physics with
Applications in the Geosciences, Physica
A: Statistical Mechanics and its Applications, 365(1-2),
211-216. Preprint.
D.T. Hristopulos, (2004a).
Anisotropic Spartan Random Field Models for Geostatistical Analysis, Advances
in Mineral Resources Management and Environmental Geotechnology,
Chania, June 2004, Greece. Pdf
preprint.
D.T. Hristopulos, (2004b).
Numerical Simulations of Spartan Gaussian Random Fields for Geostatistical
Applications on Lattices and Irregular Supports, Journal
of Computational Methods in Sciences and Engineering,
in press. Pdf
preprint.
D.T. Hristopulos, (2003a).
Renormalization Group Methods in Subsurface Hydrology: Overview and Applications
in Hydraulic Conductivity Upscaling, Advances
in Water Resources, 26(12), 1279-1308. Pdf
preprint.
D.T. Hristopulos, (2003b).
Spartan Gibbs Random Field Models for Geostatistical Applications, SIAM
Journal on Scientific Computing, 24(6), 2125-2162. Pdf
preprint.
D.T. Hristopulos, (2003c).
Permissibility of Fractal Exponents and Models of Band-Limited Two-Point Functions
for fGn and fBm random fields, Stochastic
Environmental Research and Risk Assessment, 17(3), 191-216
(2003). Pdf
preprint.
D.T. Hristopulos and T. Uesaka, (2002).
A Model of Machine-Direction Tension Variations in Paper Webs with Runnability
Applications, Journal
of Pulp and Paper Science<, 28(12), 389-394 (2002). Pdf
preprint.
D.T. Hristopulos, (2002).
New Anisotropic Covariance Models and Estimation of Anisotropic Parameters
Based on the Covariance Tensor Identity, Stochastic
Environmental Research and Risk Assessment, 16(1), 43-62.
Pdf
preprint.
D.T. Hristopulos and G. Christakos, (2001).
Practical Calculation of Non-Gaussian Multivariate Moments in Spatiotemporal
BME Analysis, Mathematical
Geology, 33(5), 543-568.
D.T. Hristopulos and G. Christakos, (1999).
Renormalization Group Analysis of Permeability Upscaling,Stochastic
Environmental Research and Risk Assessment, 13, 1-26.
D.T. Hristopulos and G. Christakos, (1997).
A Variational Calculation of the Effective Fluid Permeability of Heterogeneous
Media, Physical
Review E, 55(6), 7288-7298.
G. Christakos, D.T. Hristopulos and C.T. Miller, (1995).
Stochastic Diagrammatic Analysis of Groundwater Flow in Heterogeneous Porous
Media, Water
Resources Research, 31(7), 1687-1703.
Non-parametric Identification of Anisotropic
(Elliptic) Correlations in Spatially Distributed
Data Sets, by Arsenia Chorti and Dionissios T. Hristopulos
The relevant paper was published in IEEE Transactions on Signal Processing (October 2008).
Random fields are useful models of spatially variable quantities, such as those occurring in
environmental
processes and medical imaging. The fluctuations obtained in most natural data sets are
typically anisotropic. The parameters of anisotropy are often determined from the data by means of
empirical methods or the computationally expensive method of maximum likelihood. In this paper we
propose a systematic method for the identification of geometric (elliptic) anisotropy parameters of
scalar
fields. The proposed Covariance Hessian Identity (CHI) method is computationally efficient, non-parametric, non-iterative, and it applies
to differentiable random fields with normal or lognormal probability density functions. Our approach
uses sample based estimates of the random field spatial derivatives that we relate through closed form
expressions to the anisotropy parameters. This paper focuses on two spatial dimensions. We investigate
the performance of the method on synthetic samples with Gaussian and Matern correlations, both on
regular and irregular lattices. The systematic anisotropy detection provides an important pre-processing
stage of the data. Knowledge of the anisotropy parameters, followed by suitable rotation and rescaling
transformations restores isotropy thus allowing classical interpolation and signal processing methods to
be applied.
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