Isaac Cheng currently works on several software components of the Big Data Discovery Stack, which are essential to the efficient discovery of entities from textual documents like medical journals, patents, and other documents in the life sciences domain. He also implements components to provide performance and stability optimizations. In terms of entity types, he currently works on genes, and then proteins, amino acids, biological processes, and diseases.
Previously, Isaac worked on the Data Access Service (DAS3) enabling SIIP to query Vivisimo with facets and to query Solr with optional and configurable SQL decorators. He also worked on the Intelligent Document Gateway (IDG) for ibm.com and the Custom Call Flow (CCF) runtime software components. In the area of data management, Isaac developed the DB2 Everyplace Synchronization Server, XML Extender, and Net.Data. Isaac holds a Master of Science (Computer Science) degree and a Bachelor of Arts (Computer Science) degree, both from the University of California, Berkeley, U.S.A.