University of Minnesota, Twin Cities

• 
  Vipin Kumar, Lead PI, Regents Professor and William Norris Chair, Computer Science & Engineering
  
  Research: Data Mining, High-Performance Computing, and their applications in Climate/Ecosystems and Biomedical domains
• 
  Arindam Banerjee, McKnight Land-Grant Professor; Resident Fellow, Institute on the Environment; Computer Science & Engineering
  
  Research: Machine Learning, Data Mining, Information Theory, Convex Analysis and Optimization, and their applications in complex real world learning problems
• 
  Snigdhansu Chatterjee, Associate Professor, Statistics
  
  Research: My research interests are in statistical analysis and inference on large, complex datasets. I work on change detection, model selection and averaging, Bayesian modeling, resampling techniques, multivariate time series and nonparametric statistics as part of this project.
• 
  Joseph F. Knight, Assistant Professor, Forest Resources
  
  Research: Studying how changing land use affects both natural resources and humans. Geospatial science methods such as remote sensing, image processing, and geographic information systems (GIS).
• 
  Stefan Liess, Research Associate, Soil Water, and Climate
  
  Research: Simulation of atmospheric dynamics and climate change with general circulation models, interactions of climate and vegetation, tropical climate, predictability and sensitivity of climate, stratospheric processes
• 
  Shashi Shekhar, McKnight Distinguished University Professor, Computer Science & Engineering, Distinguished University Teaching Professor
  
  Research: Spatial Databases, Data and Knowledge Engineering, Spatial Data Mining
• 
  Peter K. Snyder, Assistant Professor, Department of Soil, Water, and Climate and the Department of Forest Resources
  
  Research: Interactions between the atmosphere and the biosphere with models, observations, and data analysis.
• 
  Michael Steinbach, Research Associate, Computer Science & Engineering
  
  Research: Data mining, Bioinformatics and Statistics. Two areas of focus are data mining for Earth science data and biological / biomedical data.

 

North Carolina State University

• 
  Nagiza F. Samatova, Associate Professor, Computer Science
  
  Research: Graph Theory and Algorithms, High Performance Data Analytics, Bioinformatics, Systems Biology, Data Management and Data Integration, Scientific and High Performance Computing, Natural Language Processing, Machine Learning
• 
  Fredrick H. M. Semazzi, Professor, Climate Modeling Laboratory
  
  Research: Climate modeling, development of nonhydrostatic, semi-implicit, semi-Lagrangian, numerical integration schemes for global atmospheric prediction models, and application of climate information for decision making. Over the last two years, he has been directing the development of a science plan for a ten-year HYVIC GEWEX International Regional Hydroclimate Project (RHP) to understand the hydroclimatic variability over Lake Victoria Basin and improve its climatic predictability and climate change projections.

 

Northeastern University

• 
  Auroop R. Ganguly, Associate Professor, Civil and Environmental Engineering
  
  Research: Climate extremes and climate change uncertainties, as well as climate impacts on the water sector. Knowledge discovery from data, broadly construed to include nonlinear dynamics, applied time series and spatial statistics, spatio-temporal data mining, econometrics, and operations research.

 

Northwestern University

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  Alok Choudhary, John G. Searle Professor and Chair Electrical Engineering and Computer Science Professor, Kellogg School of Management, Director, Center for Ultra-Scale Computing and Information Security (CUCIS)
  
  Research: High-performance computing, data intensive computing, scalable data mining, computer architecture, high-performance I/O systems and software, their applications in many domains. The design and evaluation of architectures and software systems, high-performance servers, high-performance databases and input-output and software protection and security.
• 
  Wei-keng Liao, Research Professor
  
  Research: High-performance computing, parallel I/O, parallel file systems, data mining, and data management for large-scale scientific applications.
• 
  Ankit Agrawal, Research Associate Professor
  
  Research: Data Mining, High Performance Computing,Bioinformatics, Social Media Analytics, Biomedical Informatics,Climate Informatics, Materials Informatics.

 

North Carolina A & T State University

• 
  Abdollah Homaifar, Duke Energy Eminent Professor in Electrical and Computer Engineering, Director of the Autonomous Control and Information Technology center and Campus Director of the Center for Power Electronics Systems
  
  Research: Machine learning, optimization, adaptive control, optimal control, signal processing, and soft computing and modeling.
• 
  Ali Karimodddini, Assistant Professor, Electrical and Computer Engineering
  
  Research: Large scale complexsystems, robotic swarms, cyber-physical systems, cooperative and distributed control of multi-agent systems, reliable and fault tolerant hybrid control systems, aerial robotics, flight control systems, discrete event systems, distributed optimization for coordination of multi-agent systems, hybrid modeling and control and biological systems.
• 
  Fatemeh Afghah, Assistant Professor, Electrical and Computer Engineering
  
  Research: Wireless Communication Systems, Cooperative Communication, Game Theory and Convex Optimization, Cognitive Radio Networks

 

Emeritus

• 
  Shyam Boriah, Research Associate, Computer Science & Engineering
  
  Research: spatio-temporal data mining, time series change detection, data mining foundations, and Earth science/environmental applications
• 
  Jonathan Foley, Director of the Institute on the Environment (IonE), professor and McKnight Presidential Chair in the Department of Ecology, Evolution and Behavior.
  
  Research: Complex global environmental systems and their interactions with human societies, global-scale ecological processes, global patterns of land use, the behavior of the planet’s climate and water cycles, and the sustainability of our biosphere.
• 
  Karsten Steinhaeuser, Research Associate, Computer Science & Engineering
  
  Research: Data mining and machine learning, specifically the construction and analysis of networks; community detection and prediction in networks; learning from large datasets, including parallel and distributed learning algorithms; applications of the above to climate science, environmental science and sustainability, biology, ecology, medicine, medical informatics, and social networks.