Yingjie Li, Ph.D.
About Yingjie Li, Ph.D.
Yingjie Li, Ph.D., is the Head of Knowledge Engineer at Jefferies, with extensive experience in semantic web technologies, programming languages, and database management.
Title
Yingjie Li, Ph.D. currently holds the position of Head of Knowledge Engineer at Jefferies. He has been serving in this role since 2020 in New York, New York, United States.
Company
Yingjie Li is currently working at Jefferies, where he occupies the role of Head of Knowledge Engineer. His responsibilities and contributions to this position have been ongoing since 2020.
Previous Roles at JPMorgan Chase & Co.
Prior to his current role, Yingjie Li worked at JPMorgan Chase & Co. from 2012 to 2020. He first served as an Associate from 2012 to 2015, and subsequently as Vice President - Semantic Architect Lead from 2016 to 2020 in the Greater New York City Area.
Experience in Research Positions
Yingjie Li has gained notable experience in research through various positions. He worked as a Research Scientist Contractor at Samsung in San Jose, CA in 2011. Additionally, he served as a Research Scientist Intern at Pitney Bowes in the Shelton, Connecticut Area during 2011.
Education and Expertise
Yingjie Li earned his Ph.D. in Computer Science from Lehigh University, where he studied from 2008 to 2012. His academic and professional journey has endowed him with expertise in programming languages such as Java, C, C++, JSP, PHP, Ajax, JavaScript, and XML. He possesses deep knowledge of Semantic Web technologies including RDF, RDFS, RDFa, OWL, OWL 2, SPARQL, and JENA.
Technical Skills and Tools
Yingjie Li is proficient in database management and development tools such as Oracle SQL Developer, PL/SQL Language, J2EE, and MySQL. He is also skilled in using development environments like Eclipse and JBuilder, along with web server software including Tomcat and Glassfish. His familiarity extends to Web Services technologies such as SOAP, WSDL, and UDDI.
Research Interests
Yingjie Li's research interests are diverse and include Semantic Web, Linked Open Data, Information Retrieval, Large-scale Data Integration and Query Answering, Ontology Modeling, Machine Learning, Rule-based Reasoning, and Natural Language Understanding.