SIAM Conference on Mathematical and Computational Issues in the Geosciences

June 29 – July 2, 2015
Stanford University
Stanford, California USA

Sponsored by the SIAM Activity Group on Geosciences.



On-site conference registration and sessions will take place on the Stanford University campus.  On-site registration and sessions will be located in the Frances C. Arrillaga Alumni Center.

To RSVP to the conference on Facebook and connect with other attendees, find roommates etc., please visit    

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Organizing Committee

Organizing Committee Co-Chairs
Margot Gerritsen, Stanford University, USA
Knut-Andreas Lie, SINTEF, Norway
Iuliu Sorin Pop, Eindhoven University of Technology, The Netherlands

Organizing Committee

Laurent Demanet, Massachusetts Institute of Technology, USA
Marc Hesse, University of Texas at Austin, USA
Robert Higdon, Oregon State University, USA 
Ibrahim Hoteit, King Abdullah University of Science and Technology, Saudi Arabi
Hans Kaper, Argonne National Laboratory, USA
Scott King, Virginia Tech, USA
Ulisses Mello, IBM Research, Brazil
Jennifer Suckale, Stanford University, USA
Carol S. Woodward, Lawrence Livermore National Laboratory, USA



From points of view ranging from science to public policy, there is a growing interest in modeling and simulation of geosystems and their applications. Some examples include petroleum exploration and recovery, underground waste disposal and cleanup of hazardous waste, earthquake prediction, weather prediction, and global climate change. Such modeling is fundamentally interdisciplinary; physical and mathematical modeling at appropriate scales, physical experiments, mathematical theory, probability and statistics, numerical approximations, and large-scale computational algorithms all have important roles to play.

This conference facilitates communication between scientists of varying backgrounds and work environments facing similar issues in different fields, and provides a forum in which advances in parts of the larger modeling picture can become known to those working in other parts. These kinds of interactions are needed for meaningful progress in understanding and predicting complex physical phenomena in the geosciences.


Funding Agency




SIAM and the Conference Organizing Committee wish to extend their thanks and appreciation to the U.S. National Science Foundation and the U.S. Department of Energy for their support of this conference.




Conference sponsors will be posted here when available.

If you are interested in sponsoring a conference, please visit Ways To Sponsor.



Mathematical Models in the Geosciences

  1. Atmospheric modeling
    1. Meteorology and hypermeteorology
    2. Monsoons
    3. Urban climate
  2. Biosphere modeling
  3. Cryosphere and hydrosphere modeling
    1. Glaciology
    2. Hydrology and limnology
    3. Oceanography
    4. Sea ice and ice cap
  4. Lithosphere and pedosphere modeling
    1. Geochemistry
    2. Geology
    3. Geophysics
    4. Plate tectonics and earth dynamics
    5. Soil science
    6. Volcanoes and earthquakes
  5. Climate
    1. Climate system
    2. Paleoclimate
    3. Climate change
  6. Energy resource modeling
    1. Carbon sequestration
    2. Geothermal energy
    3. Hydrogen or compressed air storage
    4. Methane hydrates
    5. Nuclear waste disposal
    6. Oil exploration and improved oil recovery
    7. Shale gas and oil
    8. Solar and wind energy
    9. Thermo-chemical storage

Mathematical Methods

  1. Mathematical modeling
    1. Fundamental modeling and scale transitions 
    2. Advanced theories and non-standard models
    3. Flow, reactions, transport and mechanical effects in complex media
  2. Computational and mathematical methods
    1. Algorithms and discretization methods
    2. Solution methods for coupled systems
    3. Error analysis and estimation
    4. Linear and nonlinear solvers
    5. Multiscale, upscaling, and model-reduction methods
    6. Mathematical analysis methods 
    7. Optimization methods
    8. Stochastic methods
    9. High-performance computing
  3. Model data and parameters
    1. Data assimilation
    2. Data classification, big data
    3. Model uncertainty
    4. Model calibration, inverse problems, uncertainty reduction
    5. Validation and verification
    6. Experiments and observations design


Important Deadlines

December 11, 2014 : Extended to January 5, 2015: Minisymposium proposals
January 15, 2015: Abstracts for contributed and minisymposium speakers

December 19, 2014: SIAM Student Travel Award and Early Career Travel Award Applications

June 1, 2015 Disconnect time is 4:00 PM EDT


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