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.

BHASKAR A | Survival Analysis and Reliability | Best Researcher Award

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Mr. BHASKAR A | Survival Analysis and Reliability | Best Researcher Award

SRM Institute of Science and Technology (SRMIST) | India

Mr. Bhaskar A is a highly accomplished academic and industry professional with over two decades of experience in mechanical engineering, manufacturing, and Agile methodologies. Currently serving as an Assistant Professor (Selection Grade) and Scrum Master at SRM Institute of Science and Technology (SRMIST), Ramapuram, he has played a pivotal role in integrating Agile practices into engineering education, mentoring teams, and enhancing organizational productivity. His educational journey includes an MBA from Annamalai University, an M.E. in Manufacturing Engineering from Madras Institute of Technology, and a B.E. in Mechanical Engineering from the University of Madras, and he is presently pursuing a part-time Ph.D. in Lean Manufacturing from Anna University. Over his career, he has held positions as an Assistant Professor at several engineering colleges and worked in industry roles including Production Engineer, contributing to process improvements and team management. Dr. Bhaskar has made significant research contributions in lean manufacturing, mechanical properties of materials, and the application of Agile methodologies, with numerous publications in journals and conferences. Beyond research and teaching, he is dedicated to continuous professional development, having completed multiple Faculty Development Programs, workshops, and online courses in project management, digital manufacturing, materials science, and other emerging technologies, reflecting his commitment to advancing knowledge and fostering innovation in engineering education.

Profiles:  Google Scholar | Linked In

Featured Publications

Alexpandian, A. S., Rajesha, M., Loganathan, P., Hariram, V., & [Y.R.]. (2023). Optimization of machining parameters to improve surface quality in the abrasive water jet cutting of AA6351 aluminium alloy. International Journal of Vehicle Structures & Systems, 15(4), 547–551.

Devaraju, A. B. A. (2025). Integrated ERP lean model for quality enhancement and operational excellence in SME based automotive mould manufacturing. Scientific Reports, 15(35979), 1–16.

Jeffrey, V. P. S. S. J. A., Govindaraj, S., Mahesh, R., Bhaskar, A., Arunkumar, K., & [R.]. (2025). Influence of Fe2O3 nanoparticle-infused waste cooking oil biodiesel on the emission, performance, and combustion aspects towards a cleaner environment. Journal of Environmental Nanotechnology, 14(3), 466–476.

Yoganjaneyulu, G., Perumal, V. S., Sivasankaran, S., Annamalai, B., & Niranjan, T. (2025). Strategic method to enhancing the formability of Nitinol foils via micro-incremental sheet forming processes and evaluation of structure–property. Metals and Materials International, 1–15.

Hepsi, B. M. J., Bhaskar, A., Rekha, R. S., & Vasanthi, P. (2024). Wear behavior of hemp-flax-glass fibre hybrid composite material. Advances in Additive Manufacturing Technologies, 75–79.