I am an innovative developer and researcher, somewhat geek, passionate about how big data and artificial intelligent can transform academic research, R&D, engineering and manufacturing.
I pride myself in being a fast learner who always keeps learning, enabling myself to quickly adapt to different domains and be updated with latest technologies.
QUALIFICATIONS AND SKILLS
- Programming Language: Python (~8 years) and shell script (~8 years)
- Cloud: Kubernetes cluster management (~1 years) and High-performance computing on CPUs or GPUs (~8 years)
- Big data: Hadoop ecosystem, Spark, HIVE (~3 years)
- Considerable Python programming experience in automating processes, Object Oriented design, ETL, building machining learning models, creating web and Qt GUIs, deploying applications, natural language processing, and computer vision
- Other domain knowledge: Physics, material science, Aerospace engineering and business (supply chain optimizaiton, SIOP, CRM)
Education
- PhD in Computational Material Science/Material Informatics, McGill University, Quebec, Canada – 2013-2019
- Bachelor and Master in Material Science, Central South University, Changsha, China - 2008-2013
Work Experience
- Pratt & Whitney Canada
- Python Developer, Data science/engineering, Analytics & information Management, 2017–present
- Develop general ELT modules to transfer data (from SAP, SQL server, WEB, etc.) to Hadoop Cluster
- Analyze data (from supply chain management, MRP, Finance, CRM, aftermarket, etc.), built and deployed dashboards and ML models
- Review and improve the quality and performance of the codes written by other developers and put them into production
- Python Developer, Data science/engineering, Analytics & information Management, 2017–present
- McGill University
- Research assistant, 2013-2019
- Develop computational pipelines to calculate the key properties for potential TBC materials for turbine blade and build a corresponding database for machine learning model to screen the ideal materials
- Build autoencoder neural network to automate material inspection
- Build LSTM neutral network to forecast the remaining useful life of the turbine engines based on their multivariate-time-series sensor data
- Research associate (part-time), 2019-present
- Design a SaaS platform for material informatics based on Compute Canada Cloud and HPC
- Manage academic cloud, database, and computation workflows/pipelines
- Apply artificial intelligent to facilitate new material discovery
- Coach master and PhD students for building computation workflows, data pipelines and CI/CD pipelines
- Assist to build AI-powered manufacturing processes for thin-film growth
- Research assistant, 2013-2019
Publications:
- See my Google scholar