Liang Hua | Computational Methods | Innovative Research Award

Prof. Liang Hua | Computational Methods | Innovative Research Award

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

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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

  • Journal: Neurocomputing

  • Year: 2025

Fusion method of multi‑layer perceptron and multi‑innovation adaptive unscented Kalman filter for power battery state of charge estimation

  • Journal: Journal of Energy Storage

  • Year: 2025

Maneuver strategy recognition technology for enemy combat aircraft based on Bayesian deep learning

  • Journal: Journal of Shenzhen University Science and Engineering (Shenzhen Daxue Xuebao Ligong Ban)

  • Year: 2025

Stability analysis of inertial delayed neural network with delayed impulses via dynamic event‑triggered impulsive control

  • Journal: Neurocomputing

  • Year: 2025

Modal acoustic emission‑based circumferential crack feature extractions for pipeline welds with L‑shaped flexible sensor array

  • Journal: Nondestructive Testing and Evaluation

  • Year: 2025

Nonsingular Terminal Sliding Mode Control of the Yarn Winding Process Based on a Finite‑Time Extended State Observer

  • Journal: IEEE Access

  • 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.

Rui Zu | Computational Methods | Best Researcher Award

Dr Rui Zu | Computational Methods | Best Researcher Award

Research Assistant , Penn State University | United States

Dr. Rui Zu is an accomplished materials scientist and optical physicist whose research spans advanced optical simulations, nonlinear optics, ferroelectric materials, and quantum-enabled devices. With a strong academic foundation from Pennsylvania State University, Columbia University, and the University of Science and Technology Beijing, he has emerged as a prominent voice in the field of complex material systems and optoelectronic engineering.

👨‍🎓Profile

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📚 Early Academic Pursuits

Dr. Zu began his academic journey at the University of Science and Technology, Beijing, earning his B.E. in Materials Physics in 2016. He then pursued a Master’s degree in Materials Science and Engineering at Columbia University, where he honed his skills in atomic-layer fabrication and microscopy. Building upon this, he earned his Ph.D. from Penn State University in 2023, where he developed novel methodologies and optical models to explore the physics of nonlinear optical responses in crystalline heterostructures.

🏢 Professional Endeavors

Following his doctoral studies, Dr. Zu joined 3M’s Display and Electronics Product Platform as a Research Engineer, where he leads efforts in optical design for display technologies, focusing on anti-glare and anti-sparkle solutions for self-emissive and near-eye displays. His work integrates advanced multi-scale simulation methods (FDTD, TMM, Fourier optics, ray tracing) with system-level optical prototyping, pushing the envelope in next-generation display performance.

🔬 Contributions and Research Focus

Dr. Zu’s work is distinguished by its depth and innovation in nonlinear optical simulation, ferroelectric materials engineering, and optical metrology. His flagship contribution is the development of the ♯SHAARP (Second Harmonic Analysis of Anisotropic Rotational Polarimetry) Mathematica-based package a pioneering simulation toolkit that addresses complex optical challenges including anisotropy, low symmetry, absorption, and dispersion in multilayer systems. He has also engineered sub-micrometer ferroelectric domain gratings and explored high-entropy materials, enabling ultraviolet harmonic generation, magneto-optical imaging, and strain-tunable photonic devices.

🌍 Impact and Influence

Dr. Zu’s research has led to publications in top-tier journals such as Science Advances, Nature Communications, PNAS, and Physical Review B, reflecting the high impact and interdisciplinary relevance of his work. His contributions have reshaped the understanding of optoelectronic behavior in correlated systems, and he continues to push forward the boundaries of materials design and characterization through collaborative research and open-source tools.

📊 Academic Citations

With a growing number of peer-reviewed publications many of which are co-authored with leaders in the field including L.-Q. Chen, V. Gopalan, and A. M. Lindenberg Dr. Zu’s work is frequently cited in domains ranging from computational photonics to solid-state physics, indicating his role as a rising authority in the study of nonlinear optical phenomena and ferroelectric materials.

🛠️ Research Skills

Dr. Zu possesses a formidable toolkit of research competencies, including:

  • Optical Simulation: FDTD, RCWA, TMM, ray tracing, Fourier-based wave propagation

  • Optical System Development: Nonlinear spectroscopy, ultrafast pump-probe, MOKE

  • Instrumentation: SEM, TEM, AFM, PFM, FTIR, Raman, Photoluminescence

  • Software and Programming: Mathematica (SHAARP), COMSOL, LabView

  • Advanced Materials Fabrication and Characterization: High-entropy materials, ferroelectrics

👨‍🏫 Teaching & Mentorship Experience

Dr. Zu has demonstrated a strong commitment to teaching and mentorship, having served as a Teaching Assistant for courses such as Crystal Anisotropy and Solid State Physics. He developed Mathematica-based modules that significantly enriched classroom engagement. Beyond formal coursework, he has mentored undergraduate researchers, including REU students, many of whom advanced to present at conferences or publish collaboratively. As a Lab Safety Officer, he also ensured the group’s operational continuity during the COVID-19 pandemic.

🏆 Awards and Honors

Dr. Zu’s excellence has been recognized with numerous awards, including:

  • 🎓 Alumni Association Dissertation Award, Penn State University (2023)

  • ✈️ Department Travel Award for Graduate Students, Penn State (2023)

  • 🏅 Renmin Principal Level Scholarship, USTB (2013)

  • 🌟 Merits Student Awards, USTB (2013, 2014)

🚀 Legacy and Future Contributions

As an innovator in optical and material physics, Dr. Rui Zu’s trajectory continues to rise. His work bridges fundamental science and industrial application, from quantum-inspired simulationsquantum-inspired simulations to real-world display technologies. With tools like SHAARP gaining traction in the research community and his growing influence in interdisciplinary materials science, Dr. Zu is poised to become a thought leader in photonics, materials design, and computational optics. His legacy will likely be defined by a continued push toward open scientific tools, educational outreach, and cross-sector impact.

Top Noted Publications

Thermodynamic theory of linear optical and electro-optical properties of ferroelectrics

  • Authors: Ross, A., Ali, M. S. M. M., Saha, A., Zu, R., Gopalan, V., Dabo, I., Chen, L.-Q.

  • Journal: Physical Review B

  • Year: 2025

Hidden domain boundary dynamics toward crystalline perfection

  • Authors: Mangu, A., Stoica, V. A., Zheng, H., Yang, T., Zhang, M., Wang, H. (Hugo), Zu, R., Nguyen, Q. L., Song, S., Das, S., Meisenheimer, P., Donoway, E., Chollet, M., Sun, Y., Turner, J. J., Freeland, J. W., Wen, H., Martin, L. W., Chen, L.-Q., Gopalan, V., Zhu, D., Cao, Y., Lindenberg, A. M.

  • Journal: Proceedings of the National Academy of Sciences (PNAS)

  • Year: 2025

Bulk photovoltaic effect and high mobility in the polar 2D semiconductor SnP₂Se₆

  • Authors: Sangwan, V. K., Chica, D. G., Chu, T.-C., Cheng, M., Quintero, M. A., Hao, S., Mead, C. E., Choi, H., Zu, R., Sheoran, J., He, J., Liu, Y., Qian, E., Laing, C. C., Kang, M.-A., Gopalan, V., Wolverton, C., Dravid, V. P., Lauhon, L. J., Hersam, M. C., Kanatzidis, M. G.

  • Journal: Science Advances

  • Year: 2024

Optical second harmonic generation in anisotropic multilayers with complete multireflection of linear and nonlinear waves using SHAARP.ml package

  • Authors: Zu, R., Wang, B., He, J., Weber, L., Saha, A., Chen, L.-Q., Gopalan, V.

  • Journal: NPJ Computational Materials

  • Year: 2024

Perspectives and progress on wurtzite ferroelectrics: Synthesis, characterization, theory, and device applications

  • Authors: Casamento, J., Baksa, S. M., Behrendt, D., Calderon, S., Goodling, D., Hayden, J., He, F., Jacques, L., Lee, S. H., Smith, W., Suceava, A., Tran, Q., Zheng, X., Zu, R., Beechem, T., Dabo, I., Dickey, E. C., Esteves, G., Gopalan, V., Henry, M. D., Ihlefeld, J. F., Jackson, T. N., Kalinin, S. V., Kelley, K. P., Liu, Y., Rappe, A. M., Redwing, J., Trolier-McKinstry, S., Maria, J.-P.

  • Journal: Applied Physics Letters

  • Year: 2024