Xu Ge | Statistical Applications in Engineering | Industrial Statistics Award

Published on by Statistics

Mr. Xu Ge | Statistical Applications in Engineering | Industrial Statistics Award

Shanghai Jiao Tong University | China

Mr. Xu Ge is a promising researcher specializing in control science, soft sensing, and intelligent systems, currently pursuing his Ph.D. at the UM-SJTU Joint Institute, Shanghai Jiao Tong University. He earned his Bachelor’s degree in Automation from the School of Mechanical Engineering and Automation at Harbin Institute of Technology (Shenzhen), where he consistently demonstrated academic excellence and technical innovation. Throughout his academic journey, Xu Ge has been recognized with numerous honors, including the prestigious National Scholarship, Topband Enterprise Scholarship, and First-Class Academic Scholarship. His university distinctions-Outstanding Student, Outstanding CYL Member, Outstanding Graduate, and Outstanding Thesis-further highlight his commitment to excellence. Xu has achieved remarkable success in national competitions, winning the ROBOCOM National First Prize, ROBOCON National Third Prize, the National Undergraduate Smart Car Competition (Outdoor Track) National Third Prize, and the National Undergraduate Mathematics Competition Provincial First Prize. His research experience reflects a strong interdisciplinary background bridging control engineering, machine learning, and system modeling. Notably, in the NSFC project “Online Estimation of Loads and Fatigue Life Prediction of Key Chassis Components under Random Driving Conditions,” he designed a soft-sensing framework that enables high-accuracy signal estimation through data-driven models and developed an embedded system for real-world vehicle testing. His collaboration with BYD on the “New Energy Vehicles Technology Program” showcased his expertise in robotics and deep learning, where he constructed datasets from BYD blade-battery modules and integrated neural networks with classical algorithms for precise robotic welding detection and operation. Xu Ge has contributed several impactful publications, including works in Mechanical Systems and Signal Processing and IEEE Transactions on Vehicular Technology, and papers accepted for presentation at IECON 2025. His accepted and submitted research covers a wide range of topics, such as vehicle sensor optimization, kernelized modeling for wheel load estimation, and battery electrochemical parameter identification through hybrid optimization methods. With his strong foundation in algorithm design, system integration, and data-driven control, Xu Ge continues to push the frontiers of intelligent mechanical systems and vehicular sensing technologies, aspiring to develop innovative, high-performance solutions that bridge theoretical advancements with industrial applications.

Profile: Google Scholar

Featured Publications

Ge, X., Li, M., Zhou, J., Qiu, Y., & Zhang, M. (2026). MMSE noncausal FIR based wheel force soft-sensing under Bernoulli-uniform prior. Mechanical Systems and Signal Processing, 242, 113601.

Ge, X., Zhang, M., Zhou, J., Chen, W., Li, X., & Li, M. (2025). Vehicle sensor configuration optimization for tire force estimation based on Min-Max SDP. In IECON 2025 – 51st Annual Conference of the IEEE Industrial Electronics Society.

Xin Chen | Statistical Applications in Engineering | Best Researcher Award

Published on by Statistics

Dr. Xin Chen | Statistical Applications in Engineering | Best Researcher Award

Hainan University | China

Dr. Xin Chen is a distinguished petroleum engineering researcher currently serving as an Associate Researcher at the School of Marine Science and Engineering, State Key Laboratory of Marine Resource Utilization in the South China Sea, Hainan University. He obtained his Bachelor’s and Master’s degrees in Petroleum and Drilling Engineering from the China University of Petroleum, East China, and earned his Doctor of Philosophy in Petroleum Engineering from the University of Alberta. His research integrates theoretical modeling and experimental analysis to address complex challenges in gas hydrate systems, marine carbon sequestration, multiphase flow thermodynamics, enhanced oil recovery, polymer modification, and well cementing technologies. Dr. Chen has contributed significantly to advancing hydrate equilibrium calculations, cement slurry stability, and hydrocarbon phase behavior modeling. His prolific academic output includes numerous publications in top-tier journals such as Chemical Engineering Science, Fluid Phase Equilibria, Construction and Building Materials, SPE Journal, Energy, and Journal of Physical Chemistry C. In addition to his journal papers, he is a co-inventor on multiple international and national patents focusing on high-temperature and low-temperature well cementing systems, thermal-thickening stabilizers, and self-generating nitrogen foamed cement technologies. Dr. Chen has actively participated in several major research projects related to CO₂ sequestration in marine sediments, advanced reservoir fluid modeling, and wellbore cementing performance optimization, collaborating with both academic and industrial partners. He also serves as a peer reviewer for leading journals including Fuel, Engineering, Petroleum Science, and Construction and Building Materials, demonstrating his commitment to maintaining high standards in scientific publishing. According to Scopus, Dr. Xin Chen’s academic profile reflects a robust research impact with an h-index of 14, 26 documents, and more than 488 citations, signifying his growing global recognition in petroleum and energy engineering research.

Profiles: Scopus | Orcid

Featured Publications

Yang, H., Li, H., Xu, H., Wang, R., Zhang, Y., Xing, L., Chen, X., Peng, L., Kang, W., & Sarsenbekuly, B. (2026). Enhanced CO2 foam stabilization with fluorescent nano polymer microspheres for improved oil recovery: Insights from microscopic and macroscopic displacement studies. Geoenergy Science and Engineering.

Jiang, H., Yang, H., Ning, C., Peng, L., Zhang, S., Chen, X., Shi, H., Wang, R., Sarsenbekuly, B., & Kang, W. (2025). Amphiphilic polymer with ultra-high salt resistance and emulsification for enhanced oil recovery in heavy oil cold recovery production. Geoenergy Science and Engineering.