Heng-Guo Zhang | Applied Mathematics | Best Researcher Award

Assoc. Prof. Dr. Heng-Guo Zhang | Applied Mathematics | Best Researcher Award

Associate Professor at Shandong University, China

Dr. Heng-Guo Zhang 🎓 is an accomplished Associate Professor at Shandong University, China 🇨🇳, specializing in Big Data and Economic Finance 📊💰. With a Ph.D. in Applied Economics and a postdoctoral fellowship in Statistics from Fudan University, his academic foundation is both broad and deep. His research bridges economics, data science, and policy, focusing on news-driven financial risks, carbon market dynamics 🌱📈, and high-dimensional time series modeling. Dr. Zhang has authored over 11 peer-reviewed articles in SCI/SSCI journals and a 2024 monograph on financial risk evaluation using big data 📘🔍. His work addresses timely global challenges such as monetary policy frictions, COVID-19 response, and carbon policy uncertainty. Passionate about data-driven policymaking and economic modeling, Dr. Zhang is a forward-looking scholar making significant contributions to modern financial analytics and risk management 📉📑.

Professional Profile 

Scopus Profile

🎓 Education

Dr. Heng-Guo Zhang has a strong interdisciplinary academic background. He earned his Ph.D. in Applied Economics from Ocean University of China (2017) 🧮, followed by a postdoctoral fellowship in Statistics at the prestigious Fudan University (2019) 📊. Prior to this, he completed his M.S. in Information Science (2011) and B.S. in Library Science (2008) from Sun Yat-sen University 🏫. His diverse educational journey across economics, statistics, and information science forms a robust foundation for his current research in economic modeling, big data analytics, and financial forecasting 📈💻.

 🏛️ Professional Experience

Dr. Zhang currently serves as an Associate Professor at the Center for Economic Research, Shandong University (since 2019) 🏛️. In this role, he leads research and mentorship in finance, particularly focusing on big data applications and economic policy analysis. With over five years of academic service, he has built a solid reputation in both teaching and publishing. His experience also includes collaborative research with scholars worldwide 🌐, contributing to high-impact journals and presenting at global conferences. His professional trajectory reflects a balance between theoretical rigor and practical relevance in economics and finance 📚💼.

🔬 Research Interest

Dr. Zhang’s research revolves around Big Data and Economic Finance 📊💵. He is particularly interested in news-driven market behavior, carbon policy uncertainty, and high-dimensional time series forecasting. His work addresses pressing global financial questions using advanced statistical models and AI-driven tools 🧠📉. Topics such as non-performing loans, monetary policy frictions, and information friction in markets form the core of his investigations. His interdisciplinary lens blends data science with economic theory, enabling more accurate predictions and policy insights. Dr. Zhang is at the forefront of leveraging technology to deepen our understanding of modern financial systems 🌍🔍.

🏅 Awards and Honors

While detailed awards are not listed, Dr. Zhang’s publication record in high-impact journals (SCI/SSCI) 📰 and his authorship of a 2024 monograph demonstrate significant scholarly achievement 📘. His ability to produce impactful, peer-reviewed work and contribute to economic literature through innovative models highlights his academic distinction. Recognition through published books and journal invitations suggests respect from the global research community 🌎. Given his trajectory, Dr. Zhang is well-positioned for prestigious accolades in the near future 🏆.

🛠️ Research Skills

Dr. Zhang possesses a broad set of research skills in econometric modeling, time series analysis, and big data integration 📈🧮. He is proficient in statistical software and programming languages suitable for financial modeling and policy analysis 💻📊. His work frequently involves nonlinear models, sparse constraints, and AI-based forecasting, indicating a strong technical toolkit. His ability to convert raw data into actionable economic insights is evident in his consistent publication of complex empirical studies. These skills make him a valuable contributor to both academic and applied economics 🧑‍💼🔧.

Publications Top Note 📝

  • An Adaptive Evolutionary Causal Dynamic Factor Model
    Authors: Wei Q., Zhang H. G.
    Year: 2025
    Source: Mathematics (SCI), 13(11):1891

  • How does news‑driven monetary policy frictions affect nonperforming loans? Taking Chinese commercial banks as an example
    Authors: Zhang H. G., Wang S., Xie Y.
    Year: 2025
    Source: The North American Journal of Economics and Finance (SSCI), 76:102353

  • News‑driven bubbles in futures markets
    Authors: Zhang H. G., Li T.
    Year: 2023
    Source: Journal of Energy Markets (SCI), 16(2):55–78

  • Does carbon policy uncertainty affect economic growth? Empirical evidence from enterprises’ industrial profits in China
    Authors: Zhang H. G., Wenti Du, Yuchi Xie
    Year: 2023
    Source: Economic Computation & Economic Cybernetics Studies & Research (SSCI), 57(3):283–294

  • Faced with COVID‑19, should the government adopt a free treatment policy? Evidence from China
    Authors: Zhang H. G.
    Year: 2022
    Source: Economic Computation & Economic Cybernetics Studies & Research (SSCI), 56(3):87–100

  • Dynamic measurement of news‑driven information friction in China’s carbon market: Theory and evidence
    Authors: Zhang H. G., Tingting Cao, Li H., Xu T.
    Year: 2021
    Source: Energy Economics (SCI), 95:104994

  • High‑Dimensional Multiple Bubbles Prediction Based on Sparse Constraints
    Authors: Zhang H. G., Wu L.
    Year: 2019
    Source: IEEE Access (SCI), 7:38356–38368

  • Can onshore spot market progress influence offshore NDF market development for the CNY?
    Authors: Su C. W., Wang K. H., Zhang H. G., Nian R.
    Year: 2019
    Source: Economic Research – Ekonomska Istraživanja (SSCI), 32(1):1621–1644

  • An online sequential learning non‑parametric value‑at‑risk model for high‑dimensional time series
    Authors: Zhang H. G., Wu L., Song Y., Su C. W., Wang Q., Su F.
    Year: 2018
    Source: Cognitive Computation (SCI), 10(2):187–200

  • Calculating Value‑at‑Risk for high‑dimensional time series using a nonlinear random mapping model
    Authors: Zhang H. G., Su C. W., Song Y., Qiu S., Xiao R., Su F.
    Year: 2017
    Source: Economic Modelling (SSCI), 67:355–367

  • Is exchange rate stability beneficial for stabilizing consumer prices in China?
    Authors: Su C. W., Zhang H. G., Chang H. L., Nian R.
    Year: 2016
    Source: The Journal of International Trade & Economic Development (SSCI), 25(6):857–879

✅ Conclusion

Dr. Heng-Guo Zhang is an emerging leader in the intersection of big data and economic finance 📈🌐. His solid academic background, strong publication record, and interdisciplinary research profile position him as a highly suitable candidate for the Best Researcher Award 🏅. His work tackles real-world problems using rigorous methodologies, contributing to both theoretical advancements and policy-making. To further strengthen his profile, increased global collaboration and award recognition could enhance his visibility. Overall, Dr. Zhang exemplifies innovation, impact, and dedication in the field of modern economics 📚💼.

Shijie Zhao | Applied Mathematics | Best Researcher Award

Assoc. Prof. Dr. Shijie Zhao | Applied Mathematics | Best Researcher Award

Associate Professor at Liaoning Technical University, China

Assoc. Prof. Dr. Shijie Zhao is a distinguished researcher and academic at the Institute of Intelligence Science and Optimization, Liaoning Technical University, China. With a Ph.D. in Optimization and Management Decisions, his expertise lies in metaheuristic optimization, multi-objective optimization, and underwater navigation and positioning. He has made significant contributions through innovative algorithm designs and novel mathematical models, particularly in high-dimensional feature selection and robust navigation techniques. Dr. Zhao has published 9 SCI-indexed journal articles and participated in over 10 nationally and provincially funded research projects. He serves as a reviewer for leading journals including those by Elsevier, Springer, and IEEE, and holds memberships in 13 professional bodies. With strong programming skills, rigorous analytical thinking, and a commitment to scientific innovation, Dr. Zhao has also earned four research awards. His work bridges theoretical mathematics and practical applications, making him a valuable contributor to the global research community in intelligent systems and optimization.

Professional Profile 

Scopus Profile
ORCID Profile

Education

Assoc. Prof. Dr. Shijie Zhao has a robust academic foundation anchored at Liaoning Technical University, China. He earned his B.S. degree in Science of Information & Computation in 2012, followed by a successive postgraduate and doctoral program in Mathematics and Applied Mathematics from 2012 to 2014. He went on to complete his Ph.D. in Optimization and Management Decisions in 2018. His educational trajectory highlights a deep commitment to the field of mathematical optimization and intelligent systems. Dr. Zhao’s academic excellence is also reflected in his ability to integrate theoretical knowledge with practical problem-solving, laying a strong foundation for his future research. His interdisciplinary approach blends pure mathematics with applied optimization techniques, making him uniquely positioned to contribute to emerging challenges in computational intelligence, machine learning, and navigation systems. His comprehensive training has equipped him with skills in advanced mathematical modeling, algorithm design, and statistical analysis—all crucial for his research trajectory.

Professional Experience

Dr. Shijie Zhao began his professional journey as a faculty member at Liaoning Technical University, where he is now serving as an Associate Professor and Director of the Institute of Intelligence Science and Optimization. Since 2012, he has progressed through a series of academic roles, including a postdoctoral tenure beginning in 2020. He has successfully led and participated in a range of scientific research projects sponsored by institutions such as the China Postdoctoral Science Foundation and the Department of Science & Technology of Liaoning Province. In addition to his teaching responsibilities, he has been actively involved in administrative, academic, and research leadership roles. Dr. Zhao has served as a reviewer for numerous high-impact international journals and conferences and has editorial roles in reputed scientific publications. His contributions to collaborative and interdisciplinary projects underscore his ability to bridge research and real-world applications, enhancing his standing as a key contributor in intelligent systems research.

Research Interest

Assoc. Prof. Dr. Shijie Zhao’s research interests lie at the intersection of intelligent optimization, computational mathematics, and advanced data analytics. He specializes in the development and enhancement of metaheuristic and multi-objective optimization algorithms, addressing both theoretical and application-driven challenges. His work has pioneered novel strategies for high-dimensional feature selection and optimization in machine learning contexts. Another key area of his focus is underwater navigation and positioning, where he has introduced innovative models for enhancing gravity navigation accuracy. With a strong foundation in mathematics, Dr. Zhao combines theoretical rigor with practical applicability, ensuring that his research contributes both to academic knowledge and technological development. His recent work explores how optimization strategies can be integrated into real-time systems, with implications in robotics, autonomous navigation, and engineering design. By addressing complex computational problems, Dr. Zhao’s research plays a vital role in driving forward the capabilities of intelligent systems and adaptive algorithms.

Award and Honor

Dr. Shijie Zhao has earned multiple accolades in recognition of his impactful contributions to scientific research and innovation. He has received four prestigious research awards for his work in intelligent systems, mathematical optimization, and applied computational modeling. His leadership in various national and provincial research initiatives has further cemented his reputation as a top-tier researcher in his domain. In addition to these honors, he has held editorial and reviewer positions for over ten internationally recognized journals, including publications by IEEE, Springer, and Elsevier—an acknowledgment of his expertise and academic integrity. Dr. Zhao is also an active member of 13 professional bodies, reflecting his global engagement and scholarly influence. His participation in high-impact collaborative projects and his growing citation index underscore the recognition and respect he commands in the research community. These honors validate his innovative spirit and unwavering dedication to advancing knowledge in mathematics and intelligent computing.

Conclusion

In conclusion, Assoc. Prof. Dr. Shijie Zhao exemplifies excellence in mathematical research, optimization theory, and intelligent system applications. His educational background, combined with over a decade of professional experience, positions him as a thought leader in his field. Through pioneering contributions to metaheuristic algorithms, multi-objective optimization, and underwater navigation, he bridges the gap between theoretical frameworks and practical technologies. His commitment to research integrity, academic service, and innovation has earned him widespread recognition and professional accolades. As an educator, leader, and scientist, Dr. Zhao’s multifaceted contributions reflect a deep dedication to advancing scientific knowledge and solving complex global challenges. His future endeavors are poised to have even greater impacts on the fields of artificial intelligence, data-driven decision-making, and intelligent navigation. With a strong publication record, a solid foundation in mathematics, and an expanding research network, Dr. Zhao continues to be a prominent and influential figure in the global academic landscape.

Publications Top Notes

  • Title: ID2TM: A Novel Iterative Double-Cross Domain-Center Transfer-Matching Method for Underwater Gravity-Aided Navigation
    Authors: Shijie Zhao, Zhiyuan Dou, Huizhong Zhu, Wei Zheng, Yifan Shen
    Year: 2025
    Source: IEEE Internet of Things Journal

  • Title: OS-BiTP: Objective sorting-informed bidomain-information transfer prediction for dynamic multiobjective optimization
    Authors: Shijie Zhao, Tianran Zhang, Lei Zhang, Jinling Song
    Year: 2025
    Source: Swarm and Evolutionary Computation

  • Title: Mirage search optimization: Application to path planning and engineering design problems
    Authors: Jiahao He, Shijie Zhao, Jiayi Ding, Yiming Wang
    Year: 2025
    Source: Advances in Engineering Software

  • Title: Twin-population Multiple Knowledge-guided Transfer Prediction Framework for Evolutionary Dynamic Multi-Objective Optimization
    Authors: Shijie Zhao, Tianran Zhang, Miao Chen, Lei Zhang
    Year: 2025
    Source: Applied Soft Computing

  • Title: VC-TpMO: V-dominance and staged dynamic collaboration mechanism based on two-population for multi- and many-objective optimization algorithm
    Authors: Shijie Zhao, Shilin Ma, Tianran Zhang, Miao Chen
    Year: 2025
    Source: Expert Systems with Applications

  • Title: A Novel Cross-Line Adaptive Domain Matching Algorithm for Underwater Gravity Aided Navigation
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2024
    Source: IEEE Geoscience and Remote Sensing Letters

  • Title: Triangulation topology aggregation optimizer: A novel mathematics-based meta-heuristic algorithm for continuous optimization and engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Liang Cai, Ronghua Yang
    Year: 2024
    Source: Expert Systems with Applications

  • Title: Improving Matching Efficiency and Out-of-Domain Positioning Reliability of Underwater Gravity Matching Navigation Based on a Novel Domain-Center Adaptive-Transfer Matching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Transactions on Instrumentation and Measurement

  • Title: A dynamic support ratio of selected feature-based information for feature selection
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2023
    Source: Engineering Applications of Artificial Intelligence

  • Title: Sea-horse optimizer: a novel nature-inspired meta-heuristic for global optimization problems
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Mengchen Wang
    Year: 2023
    Source: Applied Intelligence

  • Title: Improving the Out-of-Domain Matching Reliability and Positioning Accuracy of Underwater Gravity Matching Navigation Based on a Novel Cyclic Boundary Semisquare-Domain Researching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Sensors Journal

  • Title: A feature selection method via relevant-redundant weight
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2022
    Source: Expert Systems with Applications

  • Title: Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Miao Chen
    Year: 2022
    Source: Engineering Applications of Artificial Intelligence

  • Title: Improving Matching Efficiency and Out-of-domain Reliability of Underwater Gravity Matching Navigation Based on a Novel Soft-margin Local Semicircular-domain Re-searching Model
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2022
    Source: Remote Sensing

  • Title: Improving Matching Accuracy of Underwater Gravity Matching Navigation Based on Iterative Optimal Annulus Point Method with a Novel Grid Topology
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Aigong Xu, Huizhong Zhu
    Year: 2021
    Source: Remote Sensing

  • Title: A Novel Quantum Entanglement‐Inspired Meta‐heuristic Framework for Solving Multimodal Optimization Problems
    Authors: Shijie Zhao
    Year: 2021
    Source: Chinese Journal of Electronics

  • Title: A Novel Modified Tree‐Seed Algorithm for High‐Dimensional Optimization Problems
    Authors: Shijie Zhao
    Year: 2020
    Source: Chinese Journal of Electronics