Dr. Xin Li – Leading Researcher in Random Graph Models
Assist Prof Dr. Xin Li has held the position of Associate Professor in the School of Mechanical and Electrical Engineering at China University of Mining and Technology. Concurrently, since March 2023, he has also taken on the role of Postdoc Researcher at Zhejiang University and China University of Mining and Technology within the School of Mechanical Engineering. This dual academic engagement underscores his commitment to advancing research and contributing to the academic communities at both institutions.
Education📚
📚 Embarking on an academic journey, he pursued his passion for Mechanical Engineering at Qingdao University of Technology, earning a Bachelor of Arts degree from the School of Mechanical Engineering in the period spanning September 2012 to July 2016. Building upon this foundation, he delved deeper into the intricacies of the field at Hunan University, where he successfully completed his Ph.D. in Mechanical Engineering within the College of Mechanical and Vehicle Engineering from September 2016 to July 2022. This educational odyssey reflects his steadfast dedication to scholarly pursuits and the continual pursuit of knowledge. 🎓
Professional Profiles:
RESEARCH INTERESTS
Random Graph Models; Intelligent fault diagnosis; Machine learning; Complex systems🌞
EDITORIAL BOARD
Journal of Dynamics, Monitoring and Diagnostics
Frontiers in Mechanical Engineering
AWARDS
🏆 In recognition of his outstanding contributions to academia and research, he has been honored with a series of prestigious grants and awards. Notably, he secured the National Social Science Foundation Youth Project (62206298) for the period 2022-2025, demonstrating his prowess in the field. Further bolstering his research endeavors, he received support from the Fundamental Research Funds for the Central Universities (20230N1048) in 2023-2024. His commitment to advancing scientific knowledge is also evident through grants from the China Postdoctoral Science Foundation and the Postdoctoral Science Foundation of Zhejiang Province for the years 2023-2025. In addition, he has been recognized by the Natural Science Foundation of Jiangsu Province for the period 2023-2026, solidifying his position as a respected researcher. The accolades continue with the acknowledgment of his contributions to the academic community through the China University of Mining and Technology’s “Sailing Plan” for Young Teachers (102523236) in 2023-2024, as well as the Hunan Graduate Research Innovation Project (CX20200406) for the academic year 2021-2022. These accolades underscore his dedication and success in pushing the boundaries of knowledge in his field. 🌟
TEACHING EXPERIENCE
2023 Spring Engineering Measurement Technology
2022 Autumn Equipment health management and intelligent O&M (Graduate)
SELECTED PUBLICATIONS
Li X, Yang Y, Wu Z, et al. High-accuracy gearbox health state recognition based on graph sparse
random vector functional link network[J]. Reliability Engineering & System Safety, 2021:
108187.
Li X, Li S, Wei D, Si L, Yu K, Yan K. Dynamics Simulation-driven Fault Diagnosis of Rolling
Bearings Using Security Transfer Support Matrix Machine. Reliability Engineering & System
Safety. 2023:109882.
Li X, Cheng J, Shao H, et al. A Fusion CWSMM-based Framework for Rotating Machinery
Fault Diagnosis under Strong Interference and Imbalanced Case[J]. IEEE Transactions on
Industrial Informatics, 2021, 18(8): 5180-5189.
Li X, Shao H, Lu S, et al. Highly-efficient fault diagnosis of rotating machinery under timevarying speeds using LSISMM and small infrared thermal images[J]. IEEE Transactions on
Systems, Man and Cybernetics: Systems, 2022, 52(12): 7328-7340.
Symplectic geometry packet decomposition and its applications to gear fault diagnosis
J Cheng, Y Yang, X Li, J Cheng
Mechanical Systems and Signal Processing 174, 109096