Biological & Environmental Engineering
Soil & Water Lab
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Daniel Fuka

Email: drf28@cornell.edu
Phone: 607-255-4992
Office: B62 Riley Robb Hall
Advisor: Tammo Steenhuis
Degree Program: PhD


Background and Research Interests

Daniel has returned to school after too many years in small business research and development. His thesis research is multidisciplinary, dealing with the boundary between the earth hydrological sciences and the atmospheric sciences. While he has started many many projects, he has yet to produce an article, and it is often bet that he will never finish an article or thesis for that matter... others believe that an article finished by Daniel would be one of the warning signs of the coming of the end.

Daniel's professional life has centered around numerical and complex system modeling and high performance computing. He has developed several proprietary methodologies for forecasting electrical load (demand) for a majority of the utilities in the continental US based on forecasted weather, population, and historical electrical load. He has performed research numerically modeling vadose zone water and nitrogen transport and large-scale watershed runoff within the Pacific Northwest. One of his research interests is compiler and computer performance benchmarking, using Dr. Prentice's real world Fortran-90 benchmark suite and is making the results available to the software and compiler development communities.

Daniel's past professional positions included CSO (by title only) of ARGIS, a Rockwell Collins Company, CSO and Vice President of Weather Insight, LP. At Weather Inisight, developed the complex weather ingestion and dissemination systems used by commodities groups to base risk analysis on. In conjunction with this work, Daniel performed research in spatially based commodities modeling, ranging from electrical load forecasting for utilities and energy traders, to crop yield and quality modeling.

In Daniels previous position as a research engineer at Quetzal Computational Associates, Daniel was involved in other commodity related research and development activities. He led Quetzal's crop quality and yield forecasting program where he served as the principal investigator on a related USDA SBIR project and worked with clients in the grain transportation industry.

In addition to Daniel's research in commodities forecasting, he has worked extensively in image analysis, visualization, and numerically modeling of complex biological and biomedical systems, manipulating and distilling extremely large data bases, and building computer-based environments that allow clients access to numerical simulation results. At Quetzal, he led the research team in meshing anatomical structures and building 3D virtual reality-based visualization tools for viewing biomedical and other physical systems using VRML, the Virtual Reality Modeling Language.

As the technical lead for these projects, he has developed innovative techniques for converting data from cross-sectional images from the National Library of Medicine's Visual Human Project into surface and volume mesh representations of anatomical structures, including the heart, lungs and chest. He built software tools for viewing and analyzing VRML-based visualizations of biological systems and biomedical dynamics that are among the first of their kind. His VRML representations of pacemaker lead dynamics are among the largest created to date. His work in this area has consistently pushed the limits of available VRML viewer technology, and he has therefore played a significant role in increasing available VRML viewer capabilities.

Daniel received his MS Engineering, Biological Systems Engineering, degree from Washington State University and a Bachelor's degree in Horticulture from New Mexico State. He is actively involved in a number of professional biomedical, agricultural, and engineering societies.