TcruziSPSE Team
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Revision as of 21:37, 22 February 2010 by Pablo (Talk | contribs) (People moved to TcruziSPSE Team: People is too generic of a name, may be confused with people @ knoesis, since the full URL was wiki.knoesis.org/index.php/People. Specifying that these are the people in context of Trykipedia or TcruziSPSE would be)
Kno.e.sis Center, Wright State University
Principal Investigator:
- Amit Sheth -- Dr. Amit Sheth is the LexisNexis Ohio Eminent Scholar and a Director of the Kno.e.sis center at Wright State University. He is the Principal Investigator (PI) of this project.
Postdoc:
- Priti Parikh-- Priti is a Postdoctoral Research Fellow at the Kno.e.Sis Center with Biological Science expertise. Priti helps with development and extension of ontologies, and a query processing tool, Cuebee.
Students:
- Satya Sahoo -- led the creation of the two ontologies used in this project namely, Parasite Experiment ontology, Parasite Experiment ontology in collaboration the biology domain experts. Also created the Provenir upper-level provenance ontology that has been extended to create the Parasite Experiment ontology.
- [Vinh Nguyen]
- Ajith Ranabahu
- Pablo Mendes
Tarleton Research Group, Center for Tropical and Emerging Global Diseases(CTEGD), University of Georgia
- Rick Tarleton-- Dr. Rick Tarleton is a Distinguished Research Professor in the Department of Cellular Biology at UGA. He is also a Co-PI of this project.
- Todd Minning -- Todd is an Assitant Research Scientist at the Tarleton Research Lab. He is involved in sharing lab data and evaluation of Cuebee as per the lab requirements.
Large-Scale Distributed Information Systems (LSDIS) Lab at the University of Georgia
- Prashant Doshi-- Dr. Prashant Doshi is an assistant professor of Computer Science at UGA and a co-investigator in this project.
- Amir Asiaee -- Amir is a doctoral student in the Computer Science department of UGA and a graduate research assistant in this project.
Amir and Prashant are involved in the research and development of Cuebee, which is a system for querying biological data semantically.