Lin Zhang, PhD
About Lin Zhang, PhD
Lin Zhang, PhD, is a Senior Data Scientist at Cognite, specializing in data-driven analytics and generative AI for industrial applications. With extensive experience in power systems and data modeling, he has contributed to significant projects and developed advanced knowledge graphs throughout his career.
Work at Cognite
Lin Zhang has been working at Cognite as a Senior Data Scientist since 2022. In this role, he contributes to the analytical algorithm and data science engine of the Cognite Chart product, which facilitates a no-code environment for analyzing industrial time series data. He is also involved in AI-powered contextualization projects and engages in generative AI applications tailored for industry use. His work focuses on enhancing data-driven analytics and providing operational insights.
Previous Experience
Before joining Cognite, Lin Zhang held several positions in the energy sector. He worked at American Electric Power as a Senior System Performance Analysis Engineer from 2019 to 2022. Prior to that, he served as Director of Advanced Applications R&D and Senior Power Systems Engineer at Electric Power Group, LLC from 2018 to 2019. His earlier roles include working as a Power Systems Engineer at Electric Power Group from 2014 to 2018 and as an Application Engineering Intern at Alstom Grid in 2013.
Education and Expertise
Lin Zhang holds a Doctor of Philosophy (Ph.D.) in Power Systems from Washington State University, where he studied from 2010 to 2014. He also earned a Master's degree in Power Systems from Wuhan University from 2006 to 2008. Additionally, he obtained a Bachelor's degree in Electrical Engineering from Huazhong University of Science and Technology from 2002 to 2006. His academic background provides a strong foundation for his expertise in data science and power systems engineering.
Key Projects and Contributions
Lin Zhang has developed significant projects in his career, including one of the largest knowledge graphs based on domain knowledge concepts and relationships, utilizing standards such as RDF and OWL. He participated in the optimization problem formulation and solutions for the Hess Bakken full system optimization project. Furthermore, he developed a CIM-based Flexible Data Model (FDM) that enables users to traverse the knowledge graph and utilize GraphQL for data querying.
Research and Development Experience
Lin Zhang has a strong background in research and development. He worked as a Research Assistant at Washington State University from 2010 to 2014. His experience includes converting complex greenhouse gas emission calculations from spreadsheets to the Databricks Python environment. This work highlights his ability to integrate data science with practical applications in environmental analysis.