Daniel Okouya is a DataOps Lead with 11 years’ experience specializing in semantic technologies, knowledge graphs, and real-time distributed data processing, currently architecting scalable data-integration platforms for drug discovery at Elsevier. He blends deep academic grounding (PhD in Semantic Web and multi-agent systems) with hands-on engineering in Scala, Akka, Kafka, TigerGraph and Stardog to automate lifting heterogeneous data into FAIR, actionable knowledge graphs. Daniel has led and mentored teams to deliver real-time graph analytics, governance standards, and on-demand domain-specific knowledge products that accelerate exploratory and predictive workflows. Comfortable across research and enterprise settings—from Stanford libraries to international development banks—he uniquely pairs ontology engineering and stream-processing to make vast datasets immediately findable and interoperable. An unexpected strength is his track record of operationalizing semantic SEO and semantic search techniques to boost discoverability while preserving traceability and data provenance.
11 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Semantic Web, Multi-agent System, Service Oriented Architecture, Doctor of Philosophy (Ph.D.), Semantic Web, Multi-agent System, Service Oriented Architecture at University of Lugano
Engineer's Degree, Cognitive Science and advanced Computer sciences, Engineer's Degree, Cognitive Science and advanced Computer sciences at EPITA: Ingénierie Informatique
Contributions:80 commits, 31 PRs, 60 pushes in 3 months
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