Prof. Liang Hua | Nantong University | China
Liang Hua is a Professor at Nantong University, holding a Ph.D. and serving as a doctoral supervisor and Vice President of the university. He achieved an accelerated promotion to full professor in 2016. With over 60 technical publications more than 30 indexed by SCI or EI. He is recognized for applying machine learning to industrial automation and control systems. As principal or co-investigator, he has led more than ten national and provincial-level projects, including a Key Project of the Joint Funds of the National Natural Science Foundation of China, contributions to the National Key R&D Program “Science and Technology Winter Olympics”, and the General Program of the National Natural Science Foundation. He holds over 50 granted Chinese invention patents (18 licensed or transferred) and 7 PCT patents (including 6 US patents). His leadership and scholarly excellence have earned him over 10 prestigious provincial and ministerial-level awards. He also holds leadership roles in national research committees related to transportation education and automation.
Author Profile
Education
Liang Hua earned his Ph.D. presumably in control engineering, automation, or machine learning from a well-recognized institution in China. His doctoral research likely focused on advanced control systems for industrial applications, blending signal processing, servo systems, and machine learning methodologies. After completing his doctoral program, he rose through academic ranks at Nantong University, where he became a full professor in 2016 via an accelerated promotion track. Along the way, he deepened his expertise in intelligent control, robotics, and automation, augmented by exposure to national-level research funding and research collaboration. Participation in high-level training projects such as Jiangsu Province’s “333 High‑level Personnel Training Project” and Nantong city’s “226 High‑level Personnel Training Project” provided advanced professional development in both technical and leadership dimensions, positioning him as a recognized educator and researcher in intelligent systems and machine learning applications within industrial contexts.
Professional Experience
Professor Liang Hua has a robust academic and leadership career at Nantong University, where he serves as a doctoral supervisor and Vice President. He has led and participated in over ten national and provincial research initiatives including the National Natural Science Foundation key program and the Winter Olympics R&D program directing teams focused on industrial automation and control system innovation. Liang has supervised numerous postgraduate students, guiding them in research areas of servo control, robotics, and machine learning. In parallel, he has engaged with industry through patented technology transfer, overseeing more than 18 licensed inventions. He actively contributes to professional communities as Deputy Director of the Standardization Technical Committee of China Transportation Education Research Association and as Member of the Youth Working Committee of the Chinese Association of Automation. His dual roles in academic leadership and industry collaboration demonstrate deep experience in entrepreneurship, education management, and cross-sector research innovation.
Awards and Honors
Liang Hua’s leadership in both research and teaching has garnered over 10 provincial and ministerial awards. In 2021, he received the First Prize in the China Industry‑University‑Research Cooperation Innovation Achievement Award for the development and industrialization of industrial robot equipment based on high-performance servo control systems. The same year, he was awarded the Second Prize by the China Business Federation for precision intelligent servo control systems. Additional honors include the Special Prize of Jiangsu Education Department for innovation in electrical talent training and the First Prize in the Textile Higher Education Teaching Achievement Award. Earlier, in 2019, he earned the Technology Progress Award (Second Prize) from the China Electrical Technology Society and multiple First Prizes in textile–electrical innovation teaching. In 2018, he captured First Prize at the China International Industry Expo for a welding robot innovation, and another First Prize for energy-saving servo-driven motor systems at an industry‑university‑research collaboration award. Recognitions also include local titles such as ‘Outstanding Educator’, ‘Top Ten Outstanding Young Persons Skilled Positions’, and inclusion in Jiangsu’s “333” high‑level talent project.
Research Focus
Professor Liang Hua’s research centers on machine learning and its application to industrial automation, servo control systems, robotics, and smart machinery. He develops learning-based models to optimize performance, precision, and efficiency in high-performance servo-driven industrial robots and motion systems. His work integrates data-driven techniques, control theory, and hardware implementation resulting in over 50 Chinese invention patents and multiple PCT filings. Liang also explores interpretability and safety in AI-driven control contexts. Application domains include energy-saving industrial motors, stress‑aware robotic welding control, and servo actuation systems designed to improve reliability and productivity. His projects have practical impact: they have reached industrial deployment and technology transfer stages, typically in collaboration with enterprise partners. Through his dual focus on theoretical machine learning and practical robotics systems, Liang advances both algorithmic innovation and real-world engineering solutions.
Notable Publication
APG‑DPNet: A dual‑path network with anatomical priors for perigastric veins segmentation and varicosity quantification
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Journal: Neurocomputing
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Year: 2025
Fusion method of multi‑layer perceptron and multi‑innovation adaptive unscented Kalman filter for power battery state of charge estimation
Maneuver strategy recognition technology for enemy combat aircraft based on Bayesian deep learning
Stability analysis of inertial delayed neural network with delayed impulses via dynamic event‑triggered impulsive control
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Journal: Neurocomputing
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Year: 2025
Modal acoustic emission‑based circumferential crack feature extractions for pipeline welds with L‑shaped flexible sensor array
Nonsingular Terminal Sliding Mode Control of the Yarn Winding Process Based on a Finite‑Time Extended State Observer
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Journal: IEEE Access
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Year: 2025
Conclusion
Liang Hua exemplifies a leader at the intersection of machine learning, automation, and engineering innovation. With robust experience managing national R&D projects and translating patented research into real-world industrial systems, he serves as both educator and executive at Nantong University. His honors span national awards in control technology development and educational innovation, underscoring his impact on talent development and technical excellence. Looking ahead, Liang’s work promises to advance machine learning–driven automation in sustainable manufacturing and smart infrastructures, further bridging academic research with industry advancement and enhancing the strategic competitiveness of Chinese engineering.