Xu Ge | Statistical Applications in Engineering | Industrial Statistics Award

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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.

Mustafa Kerem Kockar | Statistical Applications in Engineering | Best Researcher Award

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Assoc Prof. Dr. Mustafa Kerem Kockar | Statistical Applications in Engineering | Best Researcher Award

Hacettepe University | Turkey

Assoc Prof. Dr. Mustafa Kerem Kockar is a Turkish engineering geologist and geotechnical expert currently serving in the Department of Civil Engineering at Hacettepe University, Ankara. He holds a B.Sc., M.Sc., and Ph.D. in Geological Engineering from Middle East Technical University (METU), where his research focused on engineering geological and geotechnical site characterization of Upper Pliocene and Quaternary deposits west of Ankara. He has also conducted research at The University of Texas at Austin and Texas A&M University. His key research interests include engineering geology, rock and soil mechanics-particularly tunnelling, dam sites, slopes, and landslides-in-situ geotechnical and seismic site characterization, dynamic and static numerical modelling of geotechnical problems, environmental geotechnology, and engineering seismology with an emphasis on ground-motion amplification, attenuation modelling, earthquake hazard assessment, and enhanced geothermal systems involving hydraulic fracturing and micro-seismic monitoring. He has authored or co-authored 47 documents and has received 650 citations with an h-index of 17, reflecting his strong contribution to the field. He has supervised several postgraduate theses on landslide monitoring, slope stability, fibre-optic methods for early warning, and solar farm foundation design. His professional experience includes academic and research roles at METU, UT Austin, Texas A&M, Gazi University’s Earthquake Engineering Research Center, and Hacettepe University. He also contributes to Turkey’s national seismology and earth-interior advisory commission under the Disaster and Emergency Management Authority (AFAD) and has provided expert consultancy on major infrastructure projects such as the Trans Anatolian Natural Gas Pipeline (TANAP) and slope-erosion surveys, showcasing his interdisciplinary expertise in geotechnical fieldwork, seismic hazard analysis, and numerical modelling.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Oner, G., Akgun, H., Koçkar, M. K., & Arslan Kelam, A. (2025). Municipal landfill site selection using TOPSIS methodology: A case study for Polatlı, Ankara, Türkiye. Bulletin of Engineering Geology and the Environment, 84(3), 126.

Arslan Kelam, A., Akgun, H., Bobet, A., & Kockar, M. K. (2025). Assessment of complex rock slope instabilities in Mudurnu, Turkey, through kinematic and dynamic analyses: A case study. Rock Mechanics and Rock Engineering, 58(2), 2223–2242.

cınar, Ö. F., Aldemir, A., Zervent, A., Yücel, O. B., Erberik, M. A., Anıl, O., & Koçkar, M. K. (2024). Fundamental period estimation of RC buildings by considering structural and non-structural damage distributions through neural network. Neural Computing and Applications, 36(3), 1329–1350.

Askan, A., Altindal, A., Aydin, M. F., Erberik, M. A., Koçkar, M. K., Tun, M., et al. (2025). Assessment of urban seismic resilience of a town in Eastern Türkiye: Turkoglu, Kahramanmaras before and after 6 February 2023 M 7.8 Kahramanmaras earthquake. Earthquake Spectra, 41(1), 146–175.

Sahin, G., Okalp, K., Koçkar, M. K., Yilmaz, M. T., Jalehforouzan, A., Temiz, F. A., et al. (2024). Development of a GIS-based predicted map of Türkiye using geological and topographical parameters: Case study for the region affected by the 6 February 2023 earthquakes. Seismological Research Letters, 95(4), 2044–2057.

Yufeng Jiang | Statistical Applications in Engineering | Best Researcher Award

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Assoc Prof. Dr. Yufeng Jiang | Statistical Applications in Engineering | Best Researcher Award

Ocean University of China | China

Assoc Prof. Dr. Yufeng Jiang is an Associate Professor at the Ocean University of China, specializing in the health monitoring and safety assessment of offshore and marine engineering structures. With a strong academic foundation from the Ocean University of China, he has dedicated his career to advancing intelligent damage diagnosis methods that can directly utilize incomplete information while maintaining high noise robustness. He innovatively developed an iterative two-stage damage identification methodology capable of simultaneously locating structural damage and assessing its severity. Dr. Jiang has designed a hardware network of fiber optic sensors for condition monitoring of deepwater pressure-resistant subsea structures and created an intelligent structural health monitoring and early warning system, which has been successfully applied in a 500-meter deep-sea mixed-transport system demonstration project. His research has led to 20 Documents , 10 patents, and collaboration on three major research projects, resulting in a citation count of 111 and an h-index of 6, reflecting the significant impact of his work. Additionally, he has contributed to two consultancy projects and maintained collaborations across multiple institutions, consistently translating innovative research into practical engineering applications. Dr. Jiang continues to advance the field of marine structural safety with a focus on applied intelligence and robust monitoring solutions.

Profiles: Scopus  | Orcid

Featured Publications

Liu, Y., Wang, S., Jiang, Y., & Du, J. (2025). A spatial deformation reconstruction method of deep-sea mining riser from sparse inclination measurements. Ocean Engineering.

Wang, C., Luo, D., Guo, Y., Zheng, Z., Jiang, Y., & Du, J. (2025). A novel stochastic model updating method for offshore platforms based on Kriging model with active learning. Ocean Engineering.

Jiang, Y., Ma, C., Wang, S., & Li, Y. (2024). A novel evolutionary algorithm for structural model updating with a hybrid initialization and multi-stage update strategy. Ocean Engineering.

Jiang, Y., Liu, Y., Wang, S., & Rakicevic, Z. (2024). Structural damage classification in offshore structures under environmental variations and measured noises using linear discrimination analysis. Structural Control and Health Monitoring.

Liu, Y., Jiang, Y., Zhao, H., Wang, S., & Han, J. (2023). Experimental investigation on vortex-induced vibration characteristics of a segmented free-hanging flexible riser. Ocean Engineering.