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.

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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.

Sidra Jubair | Machine Learning | Best Researcher Award

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Ms. Sidra Jubair | Machine Learning | Best Researcher Award

Ph.D Student at Dalian University of Technology, China📖

Dr. Sidra Jubair is a dedicated researcher in the field of applied mathematics, currently pursuing her Ph.D. at the School of Mathematical Sciences, Dalian University of Technology, China, under the supervision of Prof. Jie Yang. Her research focuses on machine learning, computational fluid dynamics, and neurocomputing. With a strong academic background and numerous high-impact publications in top-tier journals, she is committed to advancing knowledge in data-driven scientific computation.

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Education Background🎓

  1. Ph.D. in Applied Mathematics (2019 – Present)
    • Dalian University of Technology, China
    • Project: Imbalanced Data Learning through Examples and Classifiers
  2. M.Sc. in Applied Mathematics (2016 – 2018)
    • Hazara University, Pakistan
    • Supervised by Prof. Dr. Muhammad Shahzad
  3. B.Sc. in Mathematics (2011 – 2015)
    • International Islamic University, Islamabad, Pakistan

Professional Experience🌱

Dr. Sidra Jubair has extensive research experience in applied mathematics, focusing on the integration of computational intelligence with fluid dynamics. She has collaborated with researchers globally and contributed to high-impact scientific journals. Her work primarily revolves around machine learning applications in engineering and environmental sciences. Additionally, she has actively participated in international conferences and workshops, sharing her insights on topics such as neurocomputing and imbalanced data learning.

Research Interests🔬

Her research interests include:

  • Neurocomputing
  • Computational Fluid Dynamics
  • Imbalanced Data Learning
  • Machine Learning Applications in Engineering

Author Metrics

Dr. Sidra Jubair has established a strong research presence in the fields of applied mathematics, machine learning, and computational fluid dynamics. Her scholarly contributions have garnered significant recognition, with over 900 citations on Google Scholar, reflecting the impact and relevance of her work within the scientific community. She holds an H-index of 15, demonstrating the consistent influence and citation of her research, and an i10-index of 12, highlighting her ability to produce multiple highly cited publications. Dr. Jubair has published extensively in top-tier, high-impact journals, including Information Processing and Management, Alexandria Engineering Journal, and Applied Water Sciences, with impact factors reaching up to 7.4. Her research on imbalanced data learning and computational modeling has been widely acknowledged, contributing valuable insights to the advancement of data-driven scientific computation.

Publications Top Notes 📄

1. Mixed convective flow of hybrid nanofluid over a heated stretching disk with zero-mass flux using the modified Buongiorno model

  • Authors: B. Ali, N.K. Mishra, K. Rafique, S. Jubair, Z. Mahmood, S.M. Eldin
  • Journal: Alexandria Engineering Journal
  • Volume: 72
  • Pages: 83-96
  • Citations: 74
  • Year: 2023

2. Numerical simulation of the nanofluid flow consists of gyrotactic microorganism and subject to activation energy across an inclined stretching cylinder

  • Authors: H.A. Othman, B. Ali, S. Jubair, M. Yahya Almusawa, S.M. Aldin
  • Journal: Scientific Reports
  • Volume: 13, Issue 1
  • Article Number: 7719
  • Citations: 51
  • Year: 2023

3. MHD flow of nanofluid over moving slender needle with nanoparticles aggregation and viscous dissipation effects

  • Authors: B. Ali, S. Jubair, D. Fathima, A. Akhter, K. Rafique, Z. Mahmood
  • Journal: Science Progress
  • Volume: 106, Issue 2
  • Article Number: 00368504231176151
  • Citations: 42
  • Year: 2023

4. Boundary layer and heat transfer analysis of mixed convective nanofluid flow capturing the aspects of nanoparticles over a needle

  • Authors: B. Ali, S. Jubair, L.A. Al-Essa, Z. Mahmood, A. Al-Bossly, F.S. Alduais
  • Journal: Materials Today Communications
  • Volume: 35
  • Article Number: 106253
  • Citations: 38
  • Year: 2023

5. Numerical investigation of heat source induced thermal slip effect on trihybrid nanofluid flow over a stretching surface

  • Authors: B. Ali, S. Jubair, A. Aluraikan, M. Abd El-Rahman, S.M. Eldin, H.A.E.W. Khalifa
  • Journal: Results in Engineering
  • Volume: 20
  • Article Number: 101536
  • Citations: 37
  • Year: 2023

Conclusion

Dr. Sidra Jubair is a highly deserving candidate for the Best Researcher Award. Her outstanding research in applied mathematics, particularly in machine learning and computational fluid dynamics, has had a profound impact on both the academic and scientific communities. Her consistent publication in top-tier journals and strong research metrics underscore her ability to produce high-quality, impactful research. While there are opportunities for her to broaden the scope of her research through real-world applications and interdisciplinary collaborations, her current work demonstrates tremendous potential for further breakthroughs in applied mathematics and engineering.

Her dedication to advancing knowledge in data-driven scientific computation, coupled with her innovative approaches, makes her an ideal candidate for the Best Researcher Award.