Paul Cuddihy

MS, Computer Science (Rochester Institute of Technology) BA, Mathematics & Computer Science (Alfred University)

Paul Cuddihy is a senior computer scientist and software systems architect in the AI technology discipline at GE Research in Niskayuna, NY. He earned an M.S. in Computer Science from Rochester Institute of Technology.  The focus of his twenty-year career at GE Research has ranged from machine learning for medical imaging equipment diagnostics, monitoring and diagnostic techniques for commercial aircraft engines, modeling techniques for monitoring seniors living independently in their own homes, to parallel execution of simulation and prediction tasks.  Since 2015, Paul has focused primarily on semantic models, linked data, and ontology-based data access (ODBA).  Paul holds over twenty U.S. patents.

Paul is one of the creators of the open source software “Semantics Toolkit” (SemTK) which provides a simplified interface to the Semantic Web tech stack.  The toolkit originally focused on path-finding and drag-and-drop SPARQL query generation to allow non-semantic experts to explore linked data.  It also includes sophisticated mapping tools and functions for ingesting traditional tabular data into linked data.  A closed-source extension now supports OBDA across generic external data types by leveraging a service layer.

It's amazing to work at a place where the answer to just about any imaginable technical question can be answered by an expert down the hall.

Publications
  1. Cuddihy, P., McHugh, J., Williams, J.W., Mulwad, V. and Aggour, K., SemTK: A Semantics Toolkit for User-friendly SPARQL Generation and Semantic Data Management.
  2. Cuddihy, P.E., McHugh, J.D.S. and Palla, R.K.R., General Electric Co, 2017. Method and tool for browsing semantic data and creating queries using a domain/range representation. U.S. Patent 9,760,614.
  3. Williams, J.W., Cuddihy, P., McHugh, J., Aggour, K.S., Menon, A., Gustafson, S.M. and Healy, T., 2015, October. Semantics for Big Data access & integration: Improving industrial equipment design through increased data usability. In Big Data (Big Data), 2015 IEEE International Conference on (pp. 1103-1112). IEEE.
  4. Cuddihy, P., McHugh, J., Williams, J.W., Mulwad, V. and Aggour, K.S., 2017. SemTK: An Ontology-first, Open Source Semantic Toolkit for Managing and Querying Knowledge Graphs. arXiv preprint arXiv:1710.11531.
  5. McHugh, J., Cuddihy, P.E., Williams, J.W., Aggour, K.S., Kumar, V.S. and Mulwad, V., 2017, December. Integrated Access to Big Data Polystores through a Knowledge-driven Framework. In Big Data (Big Data), 2017 IEEE International Conference on (pp. 1494-1503). IEEE.

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