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.

Ding Xiangyu | Statistical Applications in Engineering | Best Researcher Award

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Prof. Ding Xiangyu | Statistical Applications in Engineering | Best Researcher Award

Nanchang Hangkong University | China

Prof. Ding Xiangyu is a distinguished scholar and the Dean of the School of Power and Energy at Nanchang University of Aeronautics, where he has established himself as a leading expert in the field of aeroengine technology and engineering. With an academic career marked by innovation, precision, and dedication, Professor Ding has devoted decades to advancing research on surface treatment and sealing structures for aeroengines, contributing significantly to the reliability, performance, and longevity of modern propulsion systems. His research has been instrumental in addressing critical challenges in high-temperature sealing, material fatigue, and efficiency optimization within the aerospace industry. Professor Ding has successfully led and participated in numerous high-impact research projects supported by prestigious funding bodies such as the Jiangxi Provincial Natural Science Foundation, the National Natural Science Foundation of China, the AVIC Independent Innovation Fund, and several defense-related horizontal projects that bridge academic theory with industrial application. His leadership and expertise have positioned him as a pivotal figure in fostering collaboration between academia, government, and the aerospace sector, driving forward China’s capabilities in aeronautical power engineering. As the chief editor of the authoritative textbook Principles of Aeroengines, Professor Ding has also made substantial contributions to the academic community by shaping the next generation of aerospace engineers and researchers. His textbook serves as a foundational reference for students and professionals alike, reflecting his deep understanding of engine thermodynamics, aerodynamics, and mechanical design. Beyond his academic and research achievements, he is widely recognized for his visionary leadership in developing the School of Power and Energy into a center of excellence for innovation and applied research. Under his guidance, the school has enhanced its focus on interdisciplinary education, experimental research, and international collaboration, aligning closely with global trends in sustainable and intelligent propulsion technologies. Professor Ding’s academic influence, technical expertise, and leadership continue to inspire advancements in the field of aeroengine engineering, contributing meaningfully to China’s aerospace progress and reinforcing his reputation as one of the foremost authorities in the field. His lifelong commitment to research excellence and educational leadership underscores his invaluable role in shaping both the technological and academic landscape of aerospace power and energy systems.

Profiles:  Orcid

Featured Publications

Wang, Y., Ding, X., Yu, S., Wang, S., Wu, Z., Yuan, Y., & Wang, C. (2025). Study on the effect of laser impact strengthening on the service performance of ZL101A aluminum alloy. Journal of Materials Engineering and Performance.

Gong, Z., Zhang, T., Chen, Y., Lu, J., Ding, X., Zhang, S., Lan, M., Shen, Y., & Wang, S. (2024). Effect of laser shock peening on stress corrosion cracking of TC4/2A14 dissimilar metal friction stir welding joints. Journal of Materials Research and Technology.

Ding, X., Zhang, J., Yu, S., Jiang, Z., Zhong, J., Ma, S., Wang, S., Li, H., & Wang, C. (2024). The effect of laser shock peening on the rotating bending fatigue resistance of S51740 stainless steel. Journal of Materials Science.

Ding, X., Li, H., Jiang, Z., Zhang, J., Ma, S., Zhong, J., Wang, S., & Wang, C. (2023). Prediction of surface residual stresses after laser shock processing on TC4 titanium alloy using different neural network agent models. Coatings.

Ding, X., Ma, S., Zhang, J., Jiang, Z., Li, H., Wang, S., Wang, C., & Zhong, J. (2023). Numerical simulation and process study on laser shock peening of 1Cr18Ni9Ti material. Crystals.

Arun Kumar Gudivada | Statistical Applications in Engineering | Best Researcher Award

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Assoc Prof. Dr. Arun Kumar Gudivada | Statistical Applications in Engineering | Best Researcher Award

Aditya University | India

Assoc. Prof. Dr. Arun Kumar, currently Associate Professor in the Department of Electronics & Communication Engineering at Aditya University, Surampalem, is an emerging researcher whose work spans VLSI, quantum computing, and quantum communication. Born in Kakinada, Andhra Pradesh, he obtained his B.Tech and M.Tech from a JNTU Kakinada–affiliated college, and earned his Ph.D. from Pondicherry University. Dr. Arun Kumar has published multiple peer-reviewed articles in well-recognized journals such as the Journal of Computational Science and Journal of Supercomputing, and has also presented at numerous international conferences. He serves as a reviewer for several Springer journals. According to his Google Scholar profile, he currently holds an h-index of 7 with a total of 129 citations across 19 published documents. His research contributions explore the theoretical and practical frontiers of quantum-enabled electronics and communication systems, seeking to bridge classical VLSI design with emerging quantum paradigms. He is committed to mentoring students and fostering collaborative research in the evolving fields of quantum technologies and nano-electronics.

Profiles: Scopus | Google Scholar

Featured Publications

Reddy, T. V., Kandadi, R., Suresh, R., Arunkumar, G. A., Kalli, S. R., & D, S. (2025). Design, modeling and comparative analysis of SRAM performance and functionality under the subthreshold regime for various technologies. 2025 Fourth International Conference on Smart Technologies, Communication …

Gudivada, A. A., Sattibabu, G., & Relangi, A. K. (2025). Power, area, and delay efficient synchronous ring counter using clock gating and multi-bit flip-flops in QCA technology. International Journal of Electronics Letters, 1–11.

Bhoopathi, A. A., R., R., Sailaja, C., Jennifer, D., & Gudivada, A. (2025). A study on microstructures and physical properties of high-entropy alloys and materials. Oxidation Communications, 48(1), 162–171.

Gudivada, A. A., Avala, E., Gummarekula, S., & Tulasi, V. R. (2025). ST-QCA based error free and area efficient 4:2 compressor design. Recent Trends in VLSI and Semiconductor Packaging, 111–118.

Noorbasha, S. K. (2024). VME-EFD: A novel framework to eliminate the electrooculogram artifact from single-channel EEGs. Biomedical Physics & Engineering Express, 11(1), 015041.

Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

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Dr. Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

C.V. Raman Global University | India

Dr. Abhijeet Das, Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar, is an accomplished civil engineering researcher specializing in watershed hydrology, hydrological modeling, climate change impact assessment, and GIS-based water resources management. With a strong academic foundation, including M.Tech and B.Tech degrees from Biju Patnaik University of Technology, he has combined rigorous research with nearly a decade of professional and teaching experience. Dr. Das has contributed extensively to collaborative national and international projects across Tunisia, USA, Oman, UK, South Africa, Syria, and Lebanon, focusing on water quality, hydrologic extremes, and sustainable water management through remote sensing, machine learning, and optimization techniques. He has published 88 documents indexed in Scopus, which have received 199 citations, achieving an h-index of 7, reflecting both productivity and the growing impact of his research contributions. His intellectual property portfolio includes over 30 patents filed in water resource engineering, geoinformatics, and environmental sustainability, showcasing innovation and applied problem-solving capacity. Dr. Das has actively engaged in more than 30 seminars, workshops, and international conferences, presenting advancements in civil and water resource engineering. His career trajectory illustrates a blend of academic excellence, applied research, and industry collaboration, making him a promising contributor to the advancement of sustainable infrastructure and water management systems.

Profiles: Scopus | Orcid

Featured Publications

Das, A. (2025). An optimization-based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance. Discover Environment.

Das, A., & Mishra, S. (2025). Reimagining biofiltration for sustainable industrial wastewater treatment. Discover Sustainability.

Das, A. (2025). A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in Mahanadi River Basin, Odisha, India. Discover Sustainability.

Das, A. (2025). Evaluation and prediction of surface water quality status for drinking purposes using integrated water quality indices, GIS approaches, and machine learning techniques. Desalination and Water Treatment.

Das, A., Mishra, S., & Tripathy, B. (2025). Bioplastics: A sustainable alternative or a hidden microplastic threat? Innovative Infrastructure Solutions.