Sean McKenna  Sean McKenna photo       

contact information

Senior Research Manager
Ireland Research Lab, Dublin, Ireland


Sean McKenna, Senior Manager for Constrained Resources and Environmental Analytics at IBM Research-Ireland, was elected by the International Association of Mathematical Geosciences (IAMG) as the 2016 Distinguished Lecturer at the recent IAMG annual meeting in Freiberg, Germany. 

The mission of the IAMG is to promote, worldwide, the advancement of mathematics, statistics and informatics in the Geosciences.  IAMG promotes international cooperation in the application and use of mathematics in geological research and technology and the extension of these pursuits to applications in engineering, environmental and planetary sciences.

Each year, IAMG selects a Distinguished Lecturer. Selection as a Distinguished Lecturer is viewed as a major honor and recognition of excellence by IAMG.  The Distinguished Lecturer must possess: (i) demonstrated ability to communicate mathematical concepts to a general geological audience, (ii) a clear enthusiasm for mathematical geology, (iii) recognition for work in their field, and (iv) established skill in working with individuals and in group discussions on geological problems.

In addition to recognizing an individual's significant contributions, this position promotes mathematical geosciences, stimulates general scientific and professional interest in these areas, expands the research scope within the IAMG community, and strengthens connections across IAMG activities.

The Distinguished Lecturer must prepare and plan lectures for both general geological audiences as well as one or more lectures on a specialized topic(s).  Anyone can attend the lectures, which are hosted by university departments and local geological societies.  IAMG provides funding for travel to presentation venues with local host organizations covering local lodging, food and transportation costs. 


Sean has NASA Earth Dataworked and published extensively on research and applications of mathematical and statistical techniques to problems in ground water modeling, optimal sampling for resource assessment, geostatistical models for decision making in environmental remediation and change identification in climate data sets.  This work has been applied to the development of geologic repositories for long-term underground storage, development of site characterization protocols using large amounts of geophysical data and spatial statistical analysis of satellite imagery.  These interests are being applied within IBM Research to improving efficiency and sustainability in areas of natural resources management and urban infrastructure systems.  Sean’s team in Ireland is working on applications including smarter water solutions, energy demand forecasting, 3-D environmental prediction tools, and high resolution weather forecasting

Sean has taught short-courses on probabilistic approaches to geologic site characterization and risk assessment, tracer testing in fractured rock aquifers, and detection of water quality anomalies from continuous monitoring data.  Sean previously served as Chair of the IAMG Distinguished Lecturer Committee, 2005 to 2012, and currently serves on the Editorial Board of the IAMG journal Mathematical Geosciences.

Sean will present one of three technical presentations at each venue:

Simulation of ground water flow in heterogeneous media 

Hydraulic conductivity in heterogeneous and fractured media can range over many orders of magnitude.  Creating numerical representations of this highly variable material property and simulating flow through in these representations is demonstrated here.  Examples from work in nuclear waste repositories also demonstrate results of inverse parameter estimation within these complex models. 

Hidden Markov Models in Environmental and Geoscience Applications 

Observations of geologic and environmental variables are often done through indirect sensing that reflect an unknown hidden state.   Hidden Markov models (HMM’s) provide a framework for learning and interpreting the hidden states through these indirect measurements. Examples of using HMM’s to improve decision making made from geophysical measurements are presented.    

Detecting Significance in Spatially Correlated Processes:

Recent developments for determining significance across spatially correlated results exploit properties of Gaussian random fields.   Applications to improving understanding of the relationships between vegetation dynamics and the El Nino Southern Oscillation (ENSO) anomalies are demonstrated.

A fourth presentation oriented to a general audience is also offered:

Smarter Planet 2.0

This presentation will explore progress to date in applying Big Data and analytic tools to improved operation of infrastructure systems and resource allocation with a focus on water and energy. 

More about IAMG:

The IAMG was established in August 1968 at the International Geological Congress in Prague. They currently have chapters in China, France, India, Canada, US, Germany and the Netherlands. The organization holds annual meetings and presents a number of annual awards as well as prestigious awards as well as supporting student chapters around the world and also funds research grants to students in graduate school or post- doctoral positions for research in the fields of mathematical geology, geomathematics, and geoinformatics.

SOURCE for Picture: NASA EarthData