Ruyi Liu | Financial Mathematics | Best Scholar Award

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Dr. Ruyi Liu | Financial Mathematics | Best Scholar Award

Researcher at The Hong Kong Polytechnic University, Australia📖

Dr. Ruyi Liu is a Research Fellow in Financial Mathematics at The Hong Kong Polytechnic University. His research focuses on pairs-trading strategies, financial mathematics, and stochastic analysis. He has contributed to high-impact journals in quantitative finance, stochastic processes, and financial derivatives pricing. With extensive experience in stochastic control and mathematical finance, he collaborates with leading researchers globally and supervises Ph.D. and Master’s students in related fields.

Profile

Scopus Profile

Orcid Profile

Google Scholar Profile

Education Background🎓

Dr. Liu obtained his Ph.D. in Statistics from Shandong University, China, in 2020, under the supervision of Prof. Zhen Wu, with a dissertation on optimal pairs-trading strategies and forward-backward stochastic differential equations. He earned his B.S. degree in Applied Mathematics from Shandong University in 2014, establishing a strong foundation in probability theory and stochastic analysis.

Professional Experience🌱

Dr. Liu is currently a Research Fellow at The Hong Kong Polytechnic University (since August 2024), working on pairs-trading strategies and financial mathematics in collaboration with Prof. Zuoquan Xu. Previously, he was a Postdoctoral Fellow (Level A) at The University of Sydney (2021–2024), where he focused on pricing of options and superannuation products with market and credit risk, under the mentorship of Prof. Marek Rutkowski. His research has influenced financial risk management, derivative pricing, and investment strategies.

Research Interests🔬

Dr. Liu’s research interests include pairs-trading strategies, financial derivatives pricing, stochastic control, forward-backward stochastic differential equations (FBSDEs), and market risk modeling. He specializes in developing optimal trading and pricing models for financial markets, incorporating stochastic volatility, credit risk, and Markov-switching models. His work provides mathematical frameworks for hedging, portfolio optimization, and financial risk management.

Author Metrics

Dr. Liu has published in top-tier journals, including Automatica, Quantitative Finance, Applied Energy, and Science China-Mathematics. His research spans financial pricing, stochastic differential equations, and optimization in trading strategies. He has multiple papers under review in high-impact journals, such as Finance & Stochastics and SIAM Journal on Financial Mathematics. His publications address key challenges in quantitative finance, risk management, and mathematical modeling.

Awards & Honors

Dr. Liu received a Chinese Postdoctoral Science Foundation Grant (AUD 70,000) for his research on pairs-trading strategies and stochastic models. He has also co-supervised students who received the University Medal for Outstanding Theses at The University of Sydney. His contributions to financial mathematics have been recognized through international conference presentations and research collaborations with leading experts in stochastic finance.
Publications Top Notes 📄

1. Well-posedness of a class of two-point boundary value problems associated with ordinary differential equations

  • Authors: R. Liu, Z. Wu
  • Journal: Advances in Difference Equations
  • Year: 2018
  • Pages: 1-12
  • Citations: 11
  • Summary: This paper investigates the well-posedness of two-point boundary value problems related to ordinary differential equations (ODEs). The authors analyze the existence, uniqueness, and stability of solutions under specific conditions. The findings contribute to a deeper understanding of differential equation theory and its applications in various mathematical and engineering contexts.

2. Pairs-Trading under Geometric Brownian Motions: An Optimal Strategy with Cutting Losses

  • Authors: R. Liu, Z. Wu, Q. Zhang
  • Journal: Automatica
  • Year: 2020
  • Volume: 115
  • Article ID: 108912
  • Citations: 10
  • Summary: This study proposes an optimal trading strategy for pairs trading under a geometric Brownian motion model. The model incorporates a cutting-loss mechanism to manage risks effectively. The authors develop a framework for determining optimal trade execution and stopping strategies in financial markets, contributing to algorithmic trading and portfolio management.

3. Well-posedness of Fully Coupled Linear Forward-Backward Stochastic Differential Equations

  • Authors: R. Liu, Z. Wu
  • Journal: Journal of Systems Science and Complexity
  • Year: 2019
  • Volume: 32
  • Issue: 3
  • Pages: 789-802
  • Citations: 5
  • Summary: The paper examines fully coupled linear forward-backward stochastic differential equations (FBSDEs). It establishes conditions for the well-posedness of these equations, including existence and uniqueness of solutions. The results are significant for financial mathematics, stochastic control, and applied probability.

4. Continuous-Time Mean-Variance Portfolio Selection under Non-Markovian Regime-Switching Model with Random Horizon

  • Authors: T. Chen, R. Liu, Z. Wu
  • Journal: Journal of Systems Science and Complexity
  • Year: 2023
  • Volume: 36
  • Issue: 2
  • Pages: 457-479
  • Citations: 4
  • Summary: This paper explores a continuous-time mean-variance portfolio selection problem within a non-Markovian regime-switching framework. It introduces a random horizon to reflect uncertain investment periods. The authors develop optimization strategies for asset allocation, with applications in quantitative finance and risk management.

5. Well-posedness and Penalization Schemes for Generalized BSDEs and Reflected Generalized BSDEs

  • Authors: L. Li, R. Liu, M. Rutkowski
  • Journal: arXiv Preprint
  • Year: 2022
  • Article ID: arXiv:2212.12854
  • Citations: 3
  • Summary: This preprint investigates the well-posedness and penalization methods for generalized backward stochastic differential equations (BSDEs) and reflected BSDEs. The authors develop analytical techniques for solving these equations, with implications in stochastic control, financial mathematics, and applied probability.

Conclusion

Dr. Ruyi Liu is an outstanding candidate for the Best Scholar Award due to his high-impact research, technical expertise, global collaborations, and mentorship efforts. His work has significantly contributed to quantitative finance, stochastic analysis, and financial mathematics. While he could further expand his industry collaborations and interdisciplinary research, his current contributions make him a strong contender for this award.

Xin Liu | Deep Learning | Best Researcher Award

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Dr. Xin Liu | Deep Learning | Best Researcher Award

Associate Professor at Wenzhou Business College, China📖

Dr. Xin Liu is an Associate Professor and Physical Education Teacher at Wenzhou Business College. With a strong academic background in physical training and deep learning, his research focuses on integrating technology with sports science to optimize athletic performance and injury prevention. His work leverages infrared thermal imaging and deep learning models to analyze heat energy expenditure in athletes. He has authored two books and actively contributes to advancing sports training methodologies through innovative research.

Profile

Orcid Profile

Education Background🎓

  • Ph.D. in Physical Education, Jose Rizal University, 2020–2023
  • Master’s in Physical Education, Shanghai Normal University, 2017–2019
  • Bachelor’s in Physical Education, Shandong Agricultural University, 2013–2017

Professional Experience🌱

  • Physical Education Teacher, Wenzhou Business College (2024–Present)
    Engaged in teaching and research on physical training methodologies, integrating AI-driven analytics in sports science.
  • Researcher in Sports Science & Deep Learning Applications
    Focused on using AI models, particularly CNN, to predict and enhance athletic performance.
Research Interests🔬
  • Physical Training & Sports Performance Optimization
  • Application of Deep Learning in Sports Science
  • Infrared Thermal Imaging for Athlete Monitoring

Author Metrics

Dr. Xin Liu has made significant contributions to the field of physical training and sports science through his research on integrating deep learning models with infrared thermal imaging technology. He has authored two books (ISBN: 978-7-5498-5469-1, 978-7-7800-2061-9) that focus on advancements in sports performance and training methodologies. His research includes two completed/ongoing projects, with findings published in reputed platforms such as Elsevier (Link). While his citation index is yet to be established, his pioneering work in applying AI-driven techniques to athlete monitoring is gaining recognition in the academic community.

Publications Top Notes 📄
Simulation of Infrared Thermal Images Based on Deep Learning in Athlete Training: Simulation of Thermal Energy Consumption
  • Authors: Xin Liu, Li Zhang, Wei Chen
  • Journal: Heliyon
  • Volume: 11
  • Issue: 1
  • Publication Date: January 2025
  • Article Number: e00823
  • DOI: Link to Article
  • Publisher: Elsevier
  • Abstract Summary: This study explores the application of deep learning techniques to simulate infrared thermal images for analyzing and predicting athletes’ thermal energy consumption. The research highlights how AI-driven thermal imaging enhances training efficiency, minimizes injury risks, and provides insights into optimizing sports performance.

Conclusion

Dr. Xin Liu is a strong candidate for the Best Researcher Award due to his innovative contributions in integrating deep learning and infrared thermal imaging in sports science. His research holds substantial potential for real-world applications, optimizing athlete performance, and advancing AI-driven monitoring techniques. With continued efforts in increasing citations, industry collaborations, and publishing in high-impact journals, he can further solidify his position as a leading researcher in the field.

Gan Xu – Artificial Intelligence – Best Researcher Award

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Gan Xu – Artificial Intelligence – Best Researcher Award

Mr. Gan Xu distinguished academic and researcher in the field Artificial Intelligence.

🌐 Professional Profile

Educations📚📚📚

He is currently pursuing a Ph.D. in Finance at the Capital University of Economics and Business in Beijing, China, since September 2021. Prior to this, he completed his Master’s in Finance from Beijing Union University, Beijing, China, graduating in June 2021. His academic journey began with a Bachelor’s degree in Biotechnology, which he obtained from Guilin Medical University, Guilin, Guangxi, China, in June 2010.

Research Experience

He participated in the Project of the National Social Science Foundation of China, focusing on the “Research on Level Measurement, Spatial and Temporal Divergence, and Improvement Path of Rural Financial Services for Rural Revitalization” (19BJY158), where he was mainly responsible for the research design of some sub-topics and participated in enterprise research. Additionally, he contributed to the Key Topic of the China Mobile Communication Federation on the “Research on the Application of Blockchain Technology in Finance” (CMCA2018ZD01), taking charge of the research design of certain sub-topics and writing research reports. Furthermore, he was involved in the research project on “Financial Support for Deepening Financial Services for Private and Micro and Small Enterprises” as part of the Comprehensive Reform Pilot City Project in Jincheng City, Shanxi Province, where he was responsible for independently participating in application writing.

Social Experience

He has co-authored several significant publications, including “Financial Density of Village Banks and Income Growth of Rural Residents” with Yang, G.Z., Xu, G., Zhang, Y., and others, published in Economic Issues in 2021. Additionally, he contributed to “Knowledge Mapping Analysis of Seven Decades of Rural Finance Research in China” with Zhang, F., Xu, G., Zhang, X.Y., and Cheng, X., which appeared in Rural Finance Research in 2020. He also co-authored “A Review of Blockchain Applications in the Financial Sector” with Zhang, F. and Cheng, X., published in Technology for Development in 2019.

Honors

  • Received Beijing Outstanding Graduates in 2020
  • Outstanding graduate of Beijing Union University in 2020
  • First Prize of Excellent Paper in the First Annual Meeting of the Financial Technology Professional Committee of the China Society for Technology Economics, 2019
  • Second Prize of Excellent Paper in the 13th China Rural Finance Development Forum, 2019
  • Second Prize of Excellent Paper of the 9th Annual Conference of China Regional Finance and Xiongnu Financial Technology Forum, 2019

📝🔬Publications📝🔬

Micheal Olaolu Arowolo – Artificial intelligence – Excellence in Innovation

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Micheal Olaolu Arowolo – Artificial intelligence – Excellence in Innovation

Dr. Micheal Olaolu Arowolo  distinguished academic and researcher in the field Artificial Intelligence. He holds several academic and professional memberships. In March 2021, he became a member of the Institute of Electrical and Electronics Engineers (IEEE), with membership number 96234988. He joined the Asia Pacific Institute of Science and Engineering (APISE) in September 2019, holding membership number M20190918110. In May 2019, he became a member of both the International Society for Computational Biology (ISCB) and the Nigerian Bioinformatics and Genomics Network (NBGN), with membership number NBGNI380. He also joined the Society of Digital Information and Wireless Communications (SDIWC) in March 2017 and the European Alliance for Innovation (EAI) in February 2017. Additionally, he has been a member of the International Association of Engineers (IAENG) since September 2015, with membership number 158851. His professional certifications include being an Oracle Database SQL Certified Expert from Oracle University, achieved in March 2014. Moreover, he is indexed on Scopus (57214819505), ORCID (0000-0002-9418-5346), and Web of Science Researcher (ABD-4157-202), all obtained in 2019.

 

🌐 Professional Profile

Educations📚📚📚

He attended several academic institutions, beginning with ECWA L.G.E.A Primary School ‘B’ in Ilorin, Kwara State, where he obtained his First School Leaving Certificate (FSLC) from 1991 to 1998. He then moved on to Modelak Science College in Ilorin, completing his Senior School Certificate Examination (SSCE) between 1998 and 2004. For his undergraduate studies, he attended Al-Hikmah University in Ilorin, Kwara State, earning a Bachelor of Science (B.Sc.) degree in Computer Science with Second Class Honors (Lower Division) from 2008 to 2012. Continuing his education, he obtained a Master of Science (M.Sc.) degree in Computer Science from Kwara State University in Malete, Kwara State, between 2014 and 2017. Finally, he completed his academic journey at Landmark University in Omu-aran, Kwara State, where he earned a Doctor of Philosophy (Ph.D.) in Computer Science from 2018 to 2021.

Work Experience:

He has held various academic and professional positions throughout his career. Since 2022, he has been serving as a Research Scholar, Instructor, and Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri, Columbia, specifically at the Christopher S. Bond Life Sciences Center. In 2021, he was a Lecturer II in the Department of Computer Science at Landmark University, Omu-Aran, Kwara State, Nigeria, and prior to that, from 2020 to 2021, he worked there as an Assistant Lecturer. From 2018 to 2020, he was a Graduate Lecturer in the Department of Computer Science at the Institute of Professional Studies, Kwara State University, Malete. In 2019, he served as an Ad-Hoc Staff for the Independent National Electoral Commission (INEC) in Nigeria, working as an Oke-Ode Ad-Hoc Registration Area Technician for the Kwara State Election. His earlier roles include being an IT Consultant at Dalayak IT Consults from 2016 to 2017, a Computer Analyst at Baylings Enterprises from 2013 to 2015, and a Computer Analyst for the Ogun-Oshun River Basin Development Authority during his National Youth Service Corps (NYSC) from November 2012 to October 2013.

Academic and Administrative Positions Held

He has served in various academic and administrative roles, including being the Academic Level Adviser for Computer Science 400L students and the Examination Officer for the Computer Science department at Landmark University from 2021 to 2022. Additionally, he was a member of the University Ranking Committee at Landmark University in 2022. He contributed to the university community by being a member of the Landmark University Sustainable Development Goal 9 group focused on industry, innovation, and infrastructure. He also served on the Local Organizing Committee (LOC) for the 2nd Nigerian Bioinformatics and Genomics Network (#NBGN21) Conference in 2021. Furthermore, he acted as the Social Director of the Al-Hikmah University Alumni Association and was an instructor for H3ABioNet’s Introduction to Bioinformatics course (IBT_2021).

His personal qualities include good logical skills, a strong personality, excellent communication abilities, keen observation, quick learning, multitasking, and proficiency in computing. Throughout his career, he has supervised over 40 undergraduate students (B.Sc.) on their projects, theses, and dissertations.

📝🔬Publications📝🔬