毕业于华东理工大学，硕士。目前担任Autodesk公司的主任工程师。他致力于推动了下一代测试策略，帮助团队在2018、2017及2016年“梅开三度”获得团队创新奖。此外，他还是 Autodesk 2019、2018 和 2017特聘的全球技术峰会的演讲嘉宾之一。
Nowadays, Autodesk is building the data@center in Cloud with all Autodesk's files such as AutoCAD, Inventor, Revit, etc. Those data are all customer data with some of description or workflows embedded. There are various source to fetch customer data and workflows such as forums, beta program, ITF online or offline activity externally and Jira, Wiki, TFS, sharepoint internally. With centralized all kinds of data and descriptions, workflows in the cloud, we are able to mapping to exist domains, modules or even features via Artificial Intelligence neuron algorithm for all kinds of files from each product. Therefore, It is become true once a data upload to server and the related workflow or feature are all predictable for engineering purpose. The platform is generate customer data or workflows to help engineering team focus on the most important cases (high frequency modules) in term of user story prioritizing, backlog grooming and release schedule shifting, sprinting, etc.