Jialing Zou | Artificial Intelligence in Petroleum Engineering | Best Researcher Award

Published on by Petroleum Engineering

Dr. Jialing Zou | Artificial Intelligence in Petroleum Engineering | Best Researcher Award

Lecturer at Southwest Petroleum University | China

Dr. Jialing Zou is a distinguished Lecturer at the School of Mechatronic Engineering, Southwest Petroleum University, recognized for her innovative contributions to intelligent sensing, data mining, and safety assessment within petroleum engineering. She holds a Ph.D. in Mechanical Engineering and focuses her research on developing intelligent early warning systems, smart fluid sensing, and real-time monitoring technologies to improve the safety and efficiency of complex drilling operations. Her scholarly pursuits combine data-driven intelligence with mechanical system optimization, advancing digital transformation and automation in the oil and gas industry. Dr. Zou has served as the principal investigator for several competitive research projects supported by major national and provincial funding agencies, including the National Natural Science Foundation of China, the Sichuan Provincial Science and Technology Department, and Southwest Petroleum University’s research initiatives. Her leadership in projects such as intelligent decision-making for digital geosteering and the development of online sensing methods for drilling fluid rheological parameters has significantly contributed to the field’s technological innovation. She has also played a key role in multiple national-level programs, including those under the National Key R&D Program of China, focusing on intelligent diagnosis and control technologies for petroleum exploration. Dr. Zou’s research has been widely published in high-impact journals 539 Citations by 460 documents 16 Documents h-index: 7 where her studies on advanced algorithms, fuzzy theory applications, and data-driven modeling have been highly regarded. Her interdisciplinary expertise bridges mechanical engineering, artificial intelligence, and safety science, positioning her as a leading emerging researcher in intelligent drilling and predictive safety systems. Through her academic excellence and commitment to innovation, Dr. Zou continues to advance knowledge, mentor young engineers, and promote the integration of intelligent technologies to enhance the sustainability and safety of petroleum engineering operations.

Profiles: Scopus | ORCID

Featured Publications

Yang, H., Liu, J., Yang, Z., Liang, H., Zhang, L., & Zou, J. (2023). Active control of the fluid pulse based on the FxLMS.

Liang, H., Xiong, J., Yang, Y., & Zou, J. (2023). Research on intelligent recognition technology in lithology based on multi-parameter fusion.

Liang, H., Xiong, J., Yang, Y., & Zou, J. (2023). Research on intelligent recognition technology in lithology based on multiparameter fusion of logging while drilling.

Liang, H., Zhang, W., Xu, W., Yang, H., & Zou, J. (2023). Research on rheological parameters correction method based on pipe viscometer.

Zhang, H., Chen, Q., Ni, P., Liang, H., Mao, M., & Zou, J. (2022). Study on the intelligent identification method of formation lithology by element and gamma spectrum.

Yang, H., Zhang, L., Li, L., Liang, H., & Zou, J. (2021). Error analysis and accuracy calibration method of U-tube Coriolis mass flowmeter under pulsating flow.

Moshu Qian | Artificial Intelligence in Petroleum Engineering | Best Academic Researcher Award

Published on by Petroleum Engineering

Prof. Moshu Qian | Artificial Intelligence in Petroleum Engineering | Best Academic Researcher Award

Full Professor at Nanjing Tech University | China

Prof. Moshu Qian, Member of IEEE, is a distinguished Full Professor at Nanjing Tech University, China, recognized for her extensive contributions to automation, intelligent systems, and control engineering. She earned her Ph.D. from Nanjing University of Aeronautics and Astronautics in 2016 and subsequently served as a visiting scholar at the University of Kent, United Kingdom, from 2019 to 2020, where she deepened her expertise in distributed control and adaptive systems. Throughout her academic career, Professor Qian has authored over 75 documents, including more than 50 peer-reviewed journal publications indexed in SCI and Scopus, and has contributed to a significant body of work that has garnered 710 citations by 624 documents, reflecting her strong research influence and visibility within the global academic community. Her current h-index is 12, attesting to the lasting impact and citation quality of her scholarly output. She has also published one academic book (ISBN: 978-7-118-11911-6) and holds 31 invention patents, many of which are applied within the industrial automation and petrochemical sectors. Professor Qian has successfully led fifteen completed and ongoing research projects and participated in four consultancy or industry-based collaborations, including the design of intelligent analysis software for lean product quality control supported by Yangzi Petrochemical in Nanjing, China. Her notable scientific achievements have earned her the First Prize of the Science and Technology Progress Award from the Chinese Society of Automation in 2023 and the Second Prize of the Science and Technology Progress Award from the Chinese Society of Instrumentation in 2024. Her research interests encompass distributed adaptive control, UAV formation systems, actuator fault-tolerant mechanisms, and smart industrial automation. Professor Qian’s scholarly dedication, innovative research, and leadership in cross-disciplinary collaborations continue to advance automation science and engineering applications, contributing to the development of intelligent, data-driven, and sustainable industrial systems that shape the future of automation and petroleum-related technologies.

Profile: Scopus | ORCID

Featured Publications

Gao, Z., Han, B., Qian, M., & Zhao, J. (2018). Active fault tolerant control for flexible spacecraft with sensor faults using adaptive integral sliding mode.

Li, J., Gao, Z., & Qian, M. (2019). Active fault tolerant control design for satellite attitude systems with mixed actuator faults.

Zhang, X., Gao, Z., Qian, M., & Bai, L. (2019). Adaptive fault-tolerant control for rigid spacecraft attitude system using fractional order sliding mode.

Bai, L., Gao, Z., Qian, M., & Zhang, X. (2019). Sliding mode observer-based FTC strategy design for satellite attitude systems with sensor fault.

Zhang, X., Gao, Z., Qian, M., & Zhou, Z. (2018). Active fault tolerant attitude control for rigid spacecraft with actuator LOE fault and saturation constraint.