Guoliang Wang | Control Science and Engineering | Best Researcher Award

Prof. Guoliang Wang | Control Science and Engineering | Best Researcher Award

 Guoliang Wang is a Professor at the Department of Automation, School of Information and Control Engineering, Liaoning Petrochemical University. 📚 With extensive expertise in control theory and automation, he has made significant contributions to Markov jump systems, stochastic system theory, and big data-driven fault detection. 🚀 He has published 86 journal articles indexed in SCI and Scopus, authored books, and holds 9 patents. 🏅 As a postdoctoral researcher at Nanjing University of Science and Technology (2011-2016), he furthered his research in control engineering. 🎓 His professional memberships include the Chinese Association of Automation and the Chinese Mathematical Society. 🏆 He has received the Liaoning Province Natural Science Academic Achievement Second Prize for his contributions. His innovative work in optimization, reinforcement learning, and system modeling continues to impact academia and industry. 🌍

Profile

Education 🎓

Guoliang Wang earned his Ph.D. in Control Theory and Control Engineering from Northeastern University (2007-2010). 🎓 Prior to that, he completed his Master’s degree in Operations Research and Control Theory at the School of Science, Northeastern University (2004-2007). 📖 His academic foundation is built on advanced mathematical modeling, stochastic systems, and automation, equipping him with expertise in complex system analysis. 🏗️ His research has consistently focused on optimizing control mechanisms and enhancing stability in dynamic environments. As a Postdoctoral Researcher at Nanjing University of Science and Technology (2011-2016), he deepened his understanding of control theory, reinforcement learning, and system dynamics. 🏅 His education has been pivotal in developing innovative methodologies for automation, fault detection, and big data-driven decision-making.

Experience 👨‍🏫

Since March 2010, Guoliang Wang has been a Professor at Liaoning Petrochemical University, specializing in automation and control engineering. 🏫 He served as Associate Dean of the Department of Automation (2013-2014), leading academic and research initiatives. 🌍 His postdoctoral research at Nanjing University of Science and Technology (2011-2016) explored stochastic system applications and control theory advancements. 🔬 Over the years, he has led multiple research projects, consulted on industrial automation solutions, and contributed to major technological advancements. 💡 His work has resulted in 86 peer-reviewed journal publications, 9 patents, and significant contributions to adaptive dynamic programming. 🚀 As a member of various professional associations, he actively collaborates with international researchers and institutions. His expertise spans Markov jump systems, stochastic modeling, fault detection, and AI-driven automation strategies

Research Interests 🔬

Guoliang Wang’s research spans modeling and control of Markov jump systems, stochastic system applications, and AI-driven automation. 🤖 His work in fault detection, diagnosis, and big data-driven prediction has led to practical advancements in system optimization. 📊 He has proposed novel stabilizing controllers, developed reinforcement learning-based optimization models, and improved system performance through convex optimization techniques. 🔍 His expertise in stochastic control extends to image processing, predictive analytics, and adaptive dynamic programming. 📡 His research contributions have significantly enhanced system stability and reduced computational complexity in industrial automation. 💡 Through collaborations with global researchers, he continues to push the boundaries of automation, AI, and smart control systems. 🚀 His work integrates theoretical insights with real-world applications, ensuring a lasting impact on engineering and technology. 🌍

Guoliang Wang has been recognized for his outstanding contributions to automation and control engineering. 🏆 He received the prestigious Liaoning Province Natural Science Academic Achievement Second Prize for his groundbreaking research. 🏅 His achievements include being a member of elite research committees such as the Youth Committee of the Chinese Association of Automation and the Adaptive Dynamic Programming and Reinforcement Learning Technical Committee. 🎖️ He has been an invited speaker at international conferences and has received commendations for his work in optimizing stochastic system control. 📜 His research impact is further reflected in his editorial board membership at the Journal of Liaoning Petrochemical University. ✍️ With numerous patents, consultancy projects, and high-impact research, he continues to receive nominations and accolades in automation, AI, and control system optimization

Publications 📚

  • Sampled-Data Stochastic Stabilization of Markovian Jump Systems via an Optimizing Mode-Separation Method

    IEEE Transactions on Cybernetics
    2025 | Journal article
    CONTRIBUTORS: Guoliang Wang; Yaqiang Lyu; Guangxing Guo
  • Stabilization of Stochastic Markovian Jump Systems via a Network-Based Controller

    IEEE Transactions on Control of Network Systems
    2024-03 | Journal article
    CONTRIBUTORS: Guoliang Wang; Siyong Song; Zhiqiang Li
  • Almost Sure Stabilization of Continuous-Time Semi-Markov Jump Systems via an Earliest Deadline First Scheduling Controller

    IEEE Transactions on Systems, Man, and Cybernetics: Systems
    2024-01 | Journal article
    CONTRIBUTORS: Guoliang Wang; Yunshuai Ren; Zhiqiang Li
  • Stability and stabilisation of Markovian jump systems under fast switching: an averaging approach

    Journal of Control and Decision
    2023-10-02 | Journal article
    CONTRIBUTORS: Guoliang Wang; Yande Zhang; Yunshuai Ren

Lichen Shi | Mechanical Engineering | Best Researcher Award

Prof. Lichen Shi | Mechanical Engineering | Best Researcher Award

 

Profile

Education

Lichen Shi (also written as Shi Lichen) is a distinguished Chinese researcher specializing in intelligent measurement, equipment status monitoring, fault diagnosis, and electromechanical system modeling. He was born on June 28, 1972, and is currently affiliated with the School of Mechanical and Electrical Engineering at Xi’an University of Architecture and Technology (XAUAT), China.

With a strong academic and research background, Professor Shi has dedicated his career to advancing intelligent measurement techniques through deep learning, as well as improving the reliability of electromechanical systems through fault diagnosis and dynamic analysis.

Academic Contributions

Professor Shi has published extensively in prestigious international journals, particularly in IEEE Sensors Journal, Measurement, and Computer Engineering & Applications. His notable works focus on deep learning-based fault diagnosis, graph neural networks, and AI-driven predictive modeling for mechanical systems.

Some of his key contributions include:

  • Developing an AI-based method for reading pointer meters using human-like reading sequences.
  • Proposing a graph neural network and Markov transform fields approach for gearbox fault diagnosis.
  • Introducing CBAM-ResNet-GCN methods for unbalance fault detection in rotating machinery.
  • Advancing domain transfer learning techniques for mixed-data gearbox fault diagnosis.
  • Pioneering a lightweight low-light object detection algorithm (CDD-YOLO) for enhanced industrial applications.

His research findings have contributed significantly to the optimization of industrial machinery, predictive maintenance, and AI-driven automation in electromechanical systems. Many of his publications are frequently cited, underlining their impact on the field.

Research Interests

Professor Shi’s research spans multiple cutting-edge areas, including:

  • Intelligent Measurement with Deep Learning
  • Equipment Status Monitoring and Fault Diagnosis
  • Electromechanical System Modeling and Dynamic Analysis

Professional Impact

As a leading expert in intelligent diagnostics and mechanical system optimization, Professor Shi has played a crucial role in bridging the gap between artificial intelligence and industrial engineering. His contributions have aided in the development of more efficient, predictive, and adaptive electromechanical systems, helping industries reduce downtime and improve operational efficiency.

Publication

  • [1] Qi Liu, Lichen Shi*. A pointer meter reading method based on human-like readingsequence and keypoint detection[J]. Measurement, 2025(248): 116994. https://doi.org/10.1016/j.measurement.2025.116994
  • [2] Haitao Wang, Zelin. Liu, Mingjun Li, Xiyang Dai, Ruihua Wang and LichenShi*. AGearbox Fault Diagnosis Method Based on Graph Neural Networks and MarkovTransform Fields[J]. IEEE Sensors Journal, 2024, 24(15) :25186-25196. doi:
    10.1109/JSEN.2024.3417231
  • [3] Haitao Wang, Xiyang Dai, Lichen Shi*, Mingjun Li, Zelin Liu, Ruihua Wang , XiaohuaXia. Data-Augmentation Based CBAM-ResNet-GCN Method for Unbalance Fault
    Diagnosis of Rotating Machinery[J]. IEEE Sensors Journal, 2024,12:34785-34799. DOI:
    10.1109/access.2024.3368755.
  • 4] Haitao Wang, Mingjun Li, Zelin Liu, Xiyang Dai, Ruihua Wang and Lichen Shi*. RotaryMachinery Fault Diagnosis Based on Split Attention MechanismandGraphConvolutional Domain Adaptive Adversarial Network[J]. IEEE Sensors Journal, 2024,
    24(4) :5399-5413. doi: 10.1109/JSEN.2023.3348597.
  • [5] Haitao Wang, Xiyang Dai, Lichen Shi*. Gearbox Fault Diagnosis Based onMixedData-Assisted Multi-Source Domain Transfer Learning under Unbalanced Data[J]. IEEESensors Journal. doi: 10.1109/JSEN.2024.3477929

 

Zihao Li | Digital Economy | Best Researcher Award

Prof. Zihao Li | Digital Economy | Best Researcher Award

 

Profile

Education

He obtained his PhD in Applied Economics from Hunan University, where he studied from September 2010 to June 2014. Prior to that, he completed his master’s degree in International Trade at Jiangnan University between September 2006 and July 2008. His academic journey began at Henan Normal University, where he earned his undergraduate degree in Economics from September 2002 to July 2006.

Work experience

Since September 2022, he has been serving as an Associate Professor, Professor, and Master Supervisor at the Business School of Nanjing University of Information Science and Technology. Prior to this, from June 2014 to August 2022, he worked at the International Business School of Henan University of Economics and Law as a Lecturer, Associate Professor, and Master Supervisor.

 

Achievement

He has authored several influential books, including Research on the Impact of Foreign Direct Investment on China’s Carbon Emissions (Economic Science Press, 2016), Foreign Direct Investment, Economic and Social Transformation and Environmental Pollution (China Financial and Economic Publishing House, 2017), and Economic and Social Transformation and Improvement of Local Government’s Environmental Governance (China Economic Publishing House, 2020).

His academic contributions have been recognized with multiple awards. He received the Third Prize of the Henan Social Science Outstanding Achievement Award (Provincial and Ministerial Level) in 2020 for his research on Environmental Governance of Local Governments with Spatial Relevance and Threshold Effect from the perspective of integrity. In 2019, he was awarded another Third Prize for his study on Local Government Tax Competition, Industrial Restructuring, and China’s Regional Green Development. Additionally, in 2016, his work on China’s Opening Up, Economic Transformation, and Low Carbon Economic Development earned him the Third Prize of the Hunan Provincial Social Science Outstanding Achievement Award.

Scientific Research Project

He has led several research projects funded by national and provincial institutions. Currently, he is hosting a General Program of the National Philosophy and Social Science Foundation (21BJY114), focusing on the Mechanism, Effect, and Policy of Digital Economy Promoting China’s Collaborative Governance of Carbon Smog (2021/9–2024/9).

Previously, he successfully completed a Youth Program of the National Philosophy and Social Science Foundation (15CGL042), which examined Anti-Corruption and Environmental Governance Improvement of Local Governments (2015/6–2019/12). He also led two provincial-level Soft Science Projects funded by the Henan Provincial Department of Science and Technology: one on Industrial Transfer and Green Development of Henan’s Industry (162400410201, 2016/6–2017/9) and another on Enterprise Green Technology Innovation and Haze Pollution Control in Henan (202400410061, 2020/1–2021/6).

 

Publication

  • (1) Zihao Li, Yue Wang, Tingting Bai. International digital trade and synergetic control of pollution and carbon emissions: Theory and evidence based on a nonlinear framework[J]. Journal of Environmental Management,2025, 376(3):124450.(SCI, JCR Q1)

    (2) Zihao Li, Bingbing Yuan, Yue Wang, Jingwen Qian, Haitao Wu. The role of digital finance on the synergistic governance of pollution & carbon: Evidence from Chinese cities[J]. Sustainable Cities and Society,2024, 115(1):105812.(SCI, JCR Q1)

    (3)李子豪,王悦.数字贸易对城市减污降碳协同发展的影响——基于产业集聚与要素配置视角[J].经济经纬,2025,(1):67-79. (CSSCI检索);

    Zihao Li, Yue Wang. The impact of digital trade on the coordinated development of urban pollution reduction and carbon reduction: based on the perspective of industrial agglomeration and factor allocation[J] Economic longitude and latitude, 2025, (1):67-79. (CSSCI)

    (4) Zihao Li, Bai Tingting, Wang Yue, Wu Haitao. The Impact of Digital Government on Corporate Green Innovation: Evidence from China[J]. Technological Forecasting and Social Change(SSCI, JCR Q1)

    (5) Tingting Bai, Yong Qi, Zihao Li, Dong Xu. Digital economy, industrial transformation and upgrading, and spatial transfer of carbon emissions: The paths for low-carbon transformation of Chinese cities[J]. Journal of Environmental Management, 2023, 344: 118528. (SCI, JCR Q1,ESI );

    (6) Bai Tingting, Qi Yong, Li Zihao*, Xu Dong. Will carbon emission trading policy improve the synergistic reduction efficiency of pollution and carbon? Evidence from216 Chinese cities[J]. Managerial and Decision Economics,2023,(8):1-24. (SSCI, JCR Q1, corresponding author);

    (7) Zihao Li, Bingbing Yuan, Tingting Bai, Dong Xu, Haitao Wu. Shooting two hawks with one arrow: The role of digitization on the coordinated development of resources and environment [J].  Resources Policy, 2024, 90(3):104827. (SSCI, JCR Q1)

    (8) Zihao Li, Xihang Xie, Xinyue Yan, Tingting Bai, Dong Xu*. Impact of China’s Rural Land Marketization on Ecological Environment Quality Based on Remote Sensing[J]. Int. J. Environ. Res. Public Health 2022, 19, 12619

    (SSCI, JCR Q1)

    (9) Zihao Li, Bai Tingting*, Tang Chang. How does the low-carbon city pilot policy affect the synergistic governance efficiency of carbon and smog? Quasi-experimental evidence from China[J]. Journal of Cleaner Production,2022(8): 133809 (SCI, JCR Q1)

    (10)李子豪,赵元,夏子谦.环保督政与地方政府碳霾协同治理绩效提升——基于环保约谈的准自然实验估计[J].中国软科学, 2023,(12):192-201. (CSSCI检索);

    Zihao Li, Yuan Zhao, Ziqian Xia. Performance improvement of coordinated governance of environmental protection supervision and local government carbon haze: quasi natural experimental estimation based on environmental interviews[J]. China Soft Science, 2023, (12): 192-201. (CSSCI)

    (11)李子豪,王倩倩.数字经济发展能否改善地区银行业风险?-基于城市商业银行的考察[J].财经论丛,2023,(12):47-57.(CSSCI);

    Zihao Li, Qianqian Wang. Can the development of digital economy improve regional banking risks- Based on the Investigation of Urban Commercial Banks [J]. Collected Essays on Finance and Economics, 2023,(12):47-57.(CSSCI)

    (12)李子豪,白婷婷.政府环保支出、绿色技术创新与雾霾污染[J].科研管理,2021,(2):52-63. (CSSCI检索, 国家自科基金委管理类A级重要期刊,《新华文摘》全文转载);

    Zihao Li, Bai Tingting. Government environmental protection expenditure, green technology innovation and smog pollution[J]. Science Research Management, 2021, (2):52-63. (CSSCI)

    (13)李子豪,袁丙兵.地方政府的雾霾治理政策作用机制: 政策工具、空间关联和门槛效应[J].资源科学, 2021,(1):40-56. (CSSCI检索);

    Zihao Li, Bingbing Yuan. Local government’s policy mechanism for haze control: policy tools, spatial correlation and threshold effect [J]. Resource science, 2021,(1):40-56. (CSSCI);

    (14)李子豪,袁丙兵.空间关联和门槛效应的地方政府环境治理研究-基于廉洁度视角的考察[J].中国软科学, 2019,(10):61-69. (CSSCI检索,国家自科基金委管理类A级重要期刊);

    Zihao Li, Bingbing Yuan. A Study on Environmental Governance of Local Government Based on Spatial Correlation and Threshold Effect: An Investigation from the Perspective of Integrity. [J]. China Soft Science, 2019, (10):61-69. (CSSCI)

    (15) Zihao Li, Mao Jun. Local Governments’ Tax Competition, Industrial Structure Adjustment and Regional Green Development in China[J]. China Finance and Economic Review,2019(1): 93-111. (ESCI);

Kaveri Hatti | Engineering| Women Researcher Award

Mrs. Kaveri Hatti | Engineering| Women Researcher Award

 

 

Profile

Education

averi Hatti is a dedicated researcher and educator in the field of VLSI Design, Embedded Systems, and Hardware Security. She is currently pursuing a Ph.D. at Amrita School of Engineering, Bangalore, focusing on FPGA-based security architectures. With a strong academic background, she holds an M.Tech in VLSI Design and Embedded Systems from VTU Regional Office, Gulbarga, and a B.Tech in Electronics and Communication Engineering from SLN College of Engineering, Raichur.

Kaveri has extensive teaching experience, having served as a Lecturer at Tagore Memorial Polytechnic College and Government Polytechnic College in Raichur before joining Amrita School of Engineering, Bangalore, as a Teaching Assistant in 2022. Her expertise lies in FPGA design, Verilog, RTL design, and hardware security implementations, utilizing tools like Xilinx ISE, VIVADO, ModelSim, and Cadence.

 

Work experience

Kaveri Hatti has a strong background in academia, with extensive teaching experience spanning several years. She began her career as a Lecturer at Tagore Memorial Polytechnic College, Raichur, from August 2009 to December 2012, where she played a key role in instructing and mentoring students in electronics and communication engineering. Simultaneously, she also served as a Lecturer at Government Polytechnic College, Raichur, from June 2009 to June 2011. Currently, she is working as a Teaching Assistant at Amrita School of Engineering, Bangalore, since February 2022, contributing to research and assisting in the academic development of students in the field of VLSI Design and Embedded Systems.

Publication