Scholar
Xiaomo Jiang
Google Scholar ID: pCV17HkAAAAJ
Dalian University of Technology
Citations & Impact
Citations
2,052
H-index
26
i10-index
52
Publications
20
Co-authors
0
Contact
No contact links provided.
Publications
Resume (English only)
Academic Achievements
- Co-authored 1 book, 5 book chapters, and nearly 100 research articles in interdisciplinary fields such as computer science, engineering, AI, and applied statistics, with over 3000 citations. Ranked as one of the top 30 most-cited Chinese scholars globally by Elsevier China Science & Technology from 2014-2018 in the field of Mechanical Engineering. Received multiple awards including patent awards, Liaoning talent award, and SAE Arch T. Colwell Merit award. Served as a peer reviewer, editorial board member, or associate editor for more than 40 different international journals and conferences. Editorial committee member of three international journals and a registered professional engineer in the state of Ohio, USA.
Research Experience
- Was a Senior Engineer, Technical Leader, and Senior Manager at the global Monitoring and Diagnostics (M&D) Center of Energy Service division at General Electric Company, leading thermal performance monitoring, analytics, diagnostics, and prognostics of combined cycle power plants, as well as pilot applications of Predix and Energy IoT in China customers and Qatar LNG plant. Served as a Senior Manager in AI analytics at Mohawk Industries, leading the successful development and deployment of an intelligent monitoring system for carpet manufacturing. Joined ENN Group in March 2019 as AI VP of Digital Energy Ltd Co and Director of Digital Research Institute, leading the incorporation of digitalization and development of AI analytics for energy IoT. Joined Dalian University of Technology (DLUT) in October 2019 and founded the Digital Twin Lab and DLUT-Shanghai Electric Joint AI Research Center.
Education
- Ph.D. in Structural Engineering from The Ohio State University; Post-doctor from Vanderbilt University.
Background
- Research interests include Energy IoT, Smart Turbomachinery, Predictive Analytics, and Probabilistic Modeling. Professional fields involve condition-based monitoring, diagnostics, AI analytics, prognostics, predictive maintenance, risk and reliability analysis, performance monitoring, Energy IoT, and model validation for engineering systems under uncertainties.
Miscellany
- Interested students are welcome to email their resumes to join the research group as graduate students or post-doctors (international students are very welcome).
Co-authors