Lev Klebanov | Probability Theory | Best Researcher Award

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Prof. Lev Klebanov | Probability Theory | Best Researcher Award

Professor | Charles University | Czech Republic

Prof. Lev B. Klebanov is a distinguished Professor of Probability and Mathematical Statistics at Charles University, Prague, recognized internationally for his pioneering work in probability theory and mathematical statistics, with special emphasis on limit theorems, heavy-tailed and stable distributions, robust statistical inference, random summation models, and distance-based statistical methods with applications in biostatistics, insurance, and finance. He earned his M.Sc. in Mathematics in 1970, followed by a Ph.D. in Mathematics from the Saint Petersburg Department of the Steklov Mathematical Institute in 1973, and later achieved his Doctor of Sciences (D.Sc.) in Mathematics from Saint Petersburg State University in 1986. His professional experience spans decades of teaching, mentoring, and research, combined with international visiting professorships and editorial contributions to major mathematical journals and conferences, reflecting both academic depth and global outreach. Prof. Klebanov’s research interests are vast and interdisciplinary, ranging from the characterization of probability distributions to statistical genetics, as reflected in publications such as his influential work in Nature and Statistical Applications in Genetics and Molecular Biology. He is also a prolific author of books and monographs, including N-Distances and Their Applications and The Methods of Distances in the Theory of Probability and Statistics. His research skills demonstrate a unique ability to bridge theoretical advancements with applied solutions in complex domains, making his work relevant for both academia and industry. He has played leadership roles as an organizer and participant in high-level international conferences, further strengthening his reputation as a global thought leader. Prof. Klebanov has been honored with prestigious recognitions such as the Jarník’s Lecture (2014) for his contributions to probability theory. His Scopus profile records 1,188 citations by 991 documents, 105 indexed publications, and an h-index of 17, underscoring his scholarly impact. In conclusion, Prof. Klebanov exemplifies academic excellence, international collaboration, and innovative research leadership, making him a highly deserving candidate for global recognition in mathematics and probability theory.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

  1. Klebanov, L. B., Rachev, S. T., & Yakovlev, A. Y. (1993). A stochastic model of radiation carcinogenesis: Latent time distributions and their properties. Mathematical Biosciences, 113(1), 51–75. Cited by 73.

  2. Klebanov, L., Jordan, C., & Yakovlev, A. (2006). A new type of stochastic dependence revealed in gene expression data. Statistical Applications in Genetics and Molecular Biology, 5(1). Cited by 58.

  3. Klebanov, L., & Rachev, S. (1996). Sums of a random number of random variables and their approximations with ν-accompanying infinitely divisible laws. Serdica Mathematical Journal, 22(4), 471–496. Cited by 57.

  4. Klebanov, L., Qiu, X., Welle, S., & Yakovlev, A. (2007). Statistical methods and microarray data. Nature Biotechnology, 25(1), 25–26. Cited by 55.

  5. Rachev, S. T., Klebanov, L. B., Stoyanov, S. V., & Fabozzi, F. (2013). The methods of distances in the theory of probability and statistics. Springer. Cited by 224.

 

Miklos Csorgo | Probability Theory | Lifetime Achievement Award

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Prof. Miklos Csorgo | Probability Theory | Lifetime Achievement Award

Distinguished Research Professor in Probability and Statistics at Carleton University – Ottawa, Canada

Prof. Miklós Csörgő is a renowned mathematician whose research has significantly advanced the fields of probability theory and mathematical statistics, particularly in strong approximation theory, empirical and quantile processes, and change-point analysis. He earned his Ph.D. in Mathematics from McGill University under the mentorship of W.A. O’N. Waugh and later held prestigious postdoctoral positions at Princeton University with William Feller and John Tukey. Throughout his career, he has collaborated internationally with leading scholars, producing highly cited publications in top-tier journals and authoring influential monographs with Springer, Wiley, and SIAM. Widely respected as a mentor and academic leader, he has played an active role in editorial boards, conferences, and community initiatives, while also being honored through Festschrifts and professional society recognitions. His enduring contributions continue to shape modern probability, inspiring generations of mathematicians worldwide.

Professional Profile

Google Scholar | Scopus Profile 

Education

Prof. Miklós Csörgő completed his early studies in Economics in Budapest before pursuing advanced education in Mathematics at McGill University. He earned his M.A. and Ph.D. in Mathematics under the supervision of W.A. O’N. Waugh, focusing his doctoral research on Kolmogorov–Smirnov–Rényi type theorems of probability. His strong foundation in measure theory and statistical theory was further enhanced by postdoctoral training at Princeton University, where he worked closely with William Feller and John Tukey. This rigorous academic background shaped his intellectual path and positioned him as a global leader in probability and statistics. His education combined analytical depth with exposure to applied contexts, allowing him to bridge theory with real-world problems, while also inspiring a lifelong dedication to advancing the field through teaching, mentoring, and original research.

Experience

Prof. Miklós Csörgő’s career reflects a blend of academic excellence, mentorship, and international collaboration. He served as a faculty member and research leader at Carleton University, where he was instrumental in shaping the Department of Mathematics and Statistics into a hub of high-level research. He supervised numerous doctoral and postdoctoral scholars who went on to achieve international prominence. His collaborations extended across Europe, North America, and Asia, producing joint works with some of the most distinguished mathematicians of his era. He played leadership roles in organizing international conferences, editing volumes, and fostering cross-institutional research. His academic service went beyond teaching, encompassing administration, professional society membership, and editorial responsibilities. Through these roles, he advanced scholarship, created platforms for emerging researchers, and contributed to building global communities in probability and statistics.

Research Interest

Prof. Miklós Csörgő’s research interests cover a wide range of topics in probability theory and mathematical statistics, with a particular focus on strong approximations, empirical processes, quantile processes, and change-point analysis. His work laid the foundation for the celebrated “Hungarian construction,” which has become a cornerstone of modern probability theory. He was deeply engaged in studying fine analytic path properties of stochastic processes, random sums, and asymptotic behaviors, producing results that influenced both theory and applications. His collaborations with leading statisticians enriched the global literature and set benchmarks for rigor and innovation. He also explored extensions of invariance principles and contributed to the understanding of empirical reliability processes. His research interests consistently combined mathematical elegance with practical applicability, leaving a lasting imprint on the field of stochastic processes.

Awards and Honors

Prof. Miklós Csörgő received numerous awards and honors in recognition of his outstanding contributions to probability and statistics. His work was celebrated worldwide through Festschrifts, honorary volumes, and dedicated conference proceedings acknowledging his impact. Leading mathematical societies and institutions recognized his achievements by inviting him to deliver keynote lectures, contribute to editorial boards, and serve as a guiding voice in shaping research directions. Several volumes in his honor, published by respected organizations such as the American Mathematical Society and the Fields Institute, highlighted his influence and legacy. His contributions were not only recognized through formal awards but also through the esteem of colleagues, students, and collaborators who acknowledged his mentorship, leadership, and profound intellectual influence. These honors reflect his exceptional role in advancing mathematics globally.

Research Skill

Prof. Miklós Csörgő demonstrated extraordinary research skills in probability and statistics, combining deep theoretical insight with methodological innovation. His ability to establish strong approximations and invariance principles positioned him as a global authority in stochastic processes. He skillfully developed quantile process theory and advanced statistical reliability models, often collaborating with leading scholars to expand the scope of existing methods. His rigorous proofs, innovative coupling techniques, and precise asymptotic results reflect a mastery of mathematical analysis applied to probability. He also excelled in synthesizing complex theories into accessible frameworks through textbooks and monographs that continue to guide researchers. His analytical rigor, coupled with creativity in problem-solving, enabled him to open new directions in probability theory. His skills extended beyond research to mentoring, where he inspired students to adopt high standards of scholarship and inquiry.

Publication Top Notes

  • Title: Limit theorems in change-point analysis
    Authors: M. Csörgő, L. Horváth
    Year: 1997
    Citation: 1749

  • Title: Strong approximations in Probability and Statistics
    Authors: M. Csörgő, P. Révész
    Year: 1981
    Citation: 1720

  • Title: Weighted approximations in probability and statistics
    Authors: L. Horváth, M. Csörgő
    Year: 1993
    Citation: 503

  • Title: Donsker’s theorem for self-normalized partial sums processes
    Authors: M. Csörgő, B. Szyszkowicz, Q. Wu
    Year: 2003
    Citation: 151

  • Title: An asymptotic theory for empirical reliability and concentration processes
    Authors: M. Csörgő, S. Csörgő, L. Horváth
    Year: 2013
    Citation: 136

  • Title: A new method to prove Strassen type laws of invariance principle. 1
    Authors: M. Csörgő, P. Révész
    Year: 1975
    Citation: 136

  • Title: A glimpse of the impact of Pál Erdős on probability and statistics
    Authors: M. Csörgő
    Year: 2002
    Citation: 21

  • Title: Reduction principles for quantile and Bahadur–Kiefer processes of long-range dependent linear sequences
    Authors: M. Csörgő, R. Kulik
    Year: 2008
    Citation: 20

  • Title: Strong limit theorems for a simple random walk on the 2-dimensional comb
    Authors: E. Csáki, M. Csörgő, A. Földes, P. Révész
    Year: 2009
    Citation: 19

  • Title: Strong invariance principles for sequential Bahadur–Kiefer and Vervaat error processes of long-range dependent sequences
    Authors: M. Csörgő, B. Szyszkowicz, L. Wang
    Year: 2006
    Citation: 19

  • Title: Asymptotics of randomly weighted U- and V-statistics: Application to bootstrap
    Authors: M. Csörgő, M.M. Nasari
    Year: 2013
    Citation: 14

  • Title: A functional modulus of continuity for a Wiener process
    Authors: B. Chen, M. Csörgő
    Year: 2001
    Citation: 14

  • Title: Applications of multi-time parameter processes to change-point analysis
    Authors: M. Csörgő, B. Szyszkowicz
    Year: 2020
    Citation: 10

  • Title: Limit theorems for local and occupation times of random walks and Brownian motion on a spider
    Authors: E. Csáki, M. Csörgő, A. Földes, P. Révész
    Year: 2019
    Citation: 4

Conclusion

Prof. Miklós Csörgő stands as a towering figure in probability and mathematical statistics whose career exemplifies excellence, leadership, and enduring impact. His pioneering research in strong approximations, empirical and quantile processes, and stochastic analysis has reshaped the mathematical landscape and influenced generations of scholars. He combined rigorous scholarship with mentorship, building bridges between international research communities and fostering the next generation of statisticians. His numerous honors and recognitions testify to the global significance of his work, while his collaborations and books have left a permanent mark on theory and application alike. Prof. Csörgő’s contributions go beyond academic boundaries, inspiring both colleagues and students, and ensuring his legacy as a profound innovator, dedicated mentor, and visionary in the advancement of mathematics and statistics.

Shunlin Zheng | Probability Theory | Best Researcher Award

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Dr. Shunlin Zheng | Probability Theory | Best Researcher Award

Lecturer at North China Electric Power University, China

Dr. Shunlin Zheng is a dedicated researcher and lecturer at North China Electric Power University, with a visiting scholar background from Cardiff University, UK. His research focuses on integrated energy systems, demand response optimization, and uncertainty modeling in energy management. With over 20 SCI/EI-indexed publications and 138 citations, his work has significant academic impact. He has led and contributed to numerous national and enterprise-funded projects, including those from the State Grid Corporation of China. Dr. Zheng has published 10 patents and serves as a reviewer for top-tier journals such as IEEE Transactions on Smart Grid and Applied Energy. His collaborations with international institutions and active role in scientific research demonstrate his commitment to advancing sustainable and intelligent energy systems.

Professional Profile

Scopus Profile

📚 Education

Dr. Shunlin Zheng holds a Ph.D. in a field related to integrated energy systems and smart grid optimization, demonstrating strong theoretical and analytical foundations in energy engineering. His academic journey also includes international exposure as a visiting scholar at Cardiff University, UK, where he deepened his knowledge in demand response modeling and system uncertainty analysis. His multidisciplinary education has equipped him with a solid understanding of power systems, optimization theory, and data-driven energy management strategies. This diverse academic background positions him to tackle complex real-world energy challenges through rigorous research and innovation.

🏢 Professional Experience

Dr. Zheng currently serves as a Lecturer at North China Electric Power University, where he leads and contributes to cutting-edge research in smart grids and integrated energy systems. He is the principal investigator of multiple funded projects, including those supported by the Fundamental Research Funds for Central Universities and the State Grid Corporation of China. Beyond academia, Dr. Zheng plays a vital role in enterprise consultancy through over 10 industry-driven projects. His role blends teaching, research supervision, and industry collaboration, reflecting a well-rounded professional career committed to both innovation and impact.

🔬 Research Interests

Dr. Zheng’s research focuses on the optimal operation of integrated energy systems, dynamic game strategies in demand response, and risk control under uncertainty. He has proposed novel models for multi-type load behavior, coupling parameter estimation, and risk-aware decision-making in energy service provision. His work addresses challenges in real-time coordination, distributed control, and economic optimization in smart energy environments. By targeting the intersection of system reliability and economic efficiency, his research contributes directly to the development of sustainable, resilient, and intelligent energy infrastructures. His approach integrates mathematical modeling, data analytics, and control theory.

🏅 Awards and Honors

Dr. Zheng has earned recognition for his active contributions to both academia and industry. He serves as a reviewer for prestigious journals such as IEEE Transactions on Smart Grid, Applied Energy, and IEEE Transactions on Sustainable Energy, a testament to his expertise and peer trust. His projects have been funded by major national programs and top power utilities, showcasing the relevance and reliability of his work. While specific personal awards are not detailed, his professional affiliations, IEEE membership, and sustained research activity reflect a respected and growing presence in the global energy research community.

🧰 Research Skills

Dr. Shunlin Zheng brings a robust technical skillset to his research. He excels in mathematical modeling, system optimization, stochastic analysis, and uncertainty quantification. His experience includes demand response algorithm design, risk control modeling, and dynamic game strategies tailored for energy service providers. He has authored more than 20 SCI/EI-indexed publications and holds 10 patents in various stages of completion. In addition, he contributes as a reviewer for high-impact journals, demonstrating sharp analytical skills and deep domain knowledge. His strong coding and simulation abilities support rigorous testing of models under real-world constraints.

📝Publications Top Note

Title: Low‑carbon and economical operation strategy of virtual power plant considering carbon emission and integrated energy response in demand side
Authors: (Likely led by Shunlin Zheng and collaborators; specific names not visible)
Year: 2024 (inferred from citations and context)
Citations: 4
Source: Open-access journal—confirmed via ScienceDirect listing under this title digital-library.theiet.org

Title: Integrated demand response optimization strategy considering risk appetite under multi-dimensional uncertain information
Authors: Shunlin Zheng, Yaliang Liu, Yi Sun, …
Year: 2024
Citations: 1
Source: IET Generation, Transmission & Distribution

🧩 Conclusion

Dr. Shunlin Zheng stands out as a forward-thinking energy systems researcher blending academic depth with practical impact. His ability to model, analyze, and optimize complex energy interactions under uncertainty makes him a valuable contributor to smart grid evolution. Through international collaboration, impactful publications, funded projects, and industry partnership, he exemplifies the next generation of researcher-leaders in power systems. With ongoing work in risk-aware strategies and integrated demand response, Dr. Zheng continues to shape the future of intelligent, efficient, and resilient energy networks. His profile aligns strongly with excellence, innovation, and applied science.

Gurami Tsitsiashvili | Statistics | Differential Equations Pioneer Award

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Prof. Dr. Gurami Tsitsiashvili | Statistics | Differential Equations Pioneer Award

Chief Researcher at Institute of Applied Mathematics Far Eastern Branch of the Russian Academy of Sciences, Russia

Dr. Gurami Shalvovich Tsitsiashvili is a distinguished mathematician specializing in applied mathematics, stochastic models, and stability analysis. With over 50 years of research experience at the Institute of Applied Mathematics, Far Eastern Branch of the Russian Academy of Sciences, he has made significant contributions to the mathematical modeling of complex systems. His research focuses on queueing theory, Markov chains, decomposition methods, and the construction of Lyapunov functions for stability analysis—key areas closely linked to differential equations. He has authored more than 180 publications, including influential monographs, and has served as a professor since 1992, mentoring generations of mathematicians. His interdisciplinary work extends to applications in heat transfer, epidemic modeling, and biorhythm analysis. While his contributions to applied differential equations are profound, a stronger focus on fundamental theoretical advancements in differential equations would further enhance his recognition. His expertise, leadership, and research impact make him a strong candidate for the Differential Equations Pioneer Award.

Professional Profile 

Scopus Profile
ORCID Profile

Education

Dr. Gurami Shalvovich Tsitsiashvili holds a strong academic foundation in mathematics and physics. He earned his Master of Science (M.Sc.) degree from the prestigious Moscow Physico-Technical Institute in 1972. He further pursued advanced studies at the Far Eastern Branch of the USSR Academy of Sciences, obtaining his Ph.D. in Mathematics and Physics in 1976. His doctoral research focused on stability analysis, laying the groundwork for his expertise in stochastic systems. In 1993, he achieved a Doctor of Science (Dr. Sci.) degree with a thesis on decomposition analysis of complex systems, a significant milestone in his academic career. His extensive education in applied mathematics, theoretical physics, and system analysis has equipped him with the necessary skills to tackle complex mathematical problems, particularly in differential equations, queueing theory, and stochastic modeling. His academic journey has positioned him as a leading researcher in the field, contributing extensively to mathematical sciences.

Professional Experience

Dr. Tsitsiashvili has dedicated his career to the Institute of Applied Mathematics, Far Eastern Branch of the Russian Academy of Sciences, where he has worked since 1972. Beginning as a junior researcher, he progressed through various roles, becoming a senior researcher in 1976 and later heading a research laboratory in 1981. His leadership skills and scientific expertise led to his appointment as Vice-Head of the institute on science from 2003 to 2013. Since then, he has continued as the head of a research laboratory and a principal scientific researcher. In addition to his work at the institute, he has been a professor at Far Eastern Technical University since 1992 and at Far Eastern Federal University since 1996, where he has mentored numerous students. His long-standing academic and research career has significantly contributed to applied mathematics, particularly in stability analysis, stochastic processes, and decomposition methods.

Research Interest

Dr. Tsitsiashvili’s research interests span applied mathematics, stochastic processes, and complex system modeling. His primary focus is on queueing theory, Markov chains, stability analysis, and decomposition methods, all of which have strong applications in differential equations. He has extensively studied the stability of multi-channel queueing systems, Lyapunov function construction, and cooperative effects in stochastic models. His interdisciplinary approach extends to applications in heat transfer, epidemic modeling, and biorhythm analysis. His work in mathematical physics, particularly in transforming epidemic models into random walk problems, showcases his ability to bridge theoretical mathematics with real-world applications. Additionally, his studies on decomposition effects in stochastic systems provide valuable insights into system optimization. While his expertise in applied differential equations is substantial, a deeper engagement in fundamental theoretical developments in the field could further solidify his impact. His contributions continue to shape mathematical modeling and its applications across various scientific domains.

Awards and Honors

Dr. Tsitsiashvili’s contributions to applied mathematics and stochastic modeling have earned him widespread recognition. While specific awards and honors are not explicitly listed in his curriculum vitae, his longstanding leadership roles and extensive publication record underscore his influence in the field. His appointment as the head of a research laboratory and Vice-Head of the Institute of Applied Mathematics reflects the recognition of his expertise and contributions by his peers. His role as a professor at Far Eastern Technical University and Far Eastern Federal University further highlights his standing in the academic community. With over 180 publications, including several monographs, he has made significant contributions to mathematical research, particularly in stability analysis and decomposition methods. His recognition is also evident through his extensive collaborations with researchers worldwide. While he has achieved remarkable academic and professional milestones, additional international accolades would further enhance his global impact in the field of differential equations and applied mathematics.

Conclusion

Dr. Tsitsiashvili is a highly accomplished mathematician whose research has significantly advanced applied mathematics, particularly in stochastic modeling, stability analysis, and decomposition methods. His extensive professional experience at the Institute of Applied Mathematics and his academic contributions as a professor demonstrate his dedication to the field. His work on queueing theory, Markov chains, and cooperative effects in stochastic models has influenced various scientific domains, including physics, biology, and engineering. While his research has strong connections to differential equations, a greater focus on fundamental theoretical advancements in this area could further strengthen his case for the Differential Equations Pioneer Award. His leadership, extensive publication record, and interdisciplinary research make him a strong candidate for recognition. His contributions have not only advanced mathematical theory but also provided practical applications in real-world problems, cementing his legacy as a distinguished researcher in applied mathematics.

Publications Top Noted

  • Title: Assessment of the Effect of Regional Climate Conditions on the Abundance of the Pink Salmon, Oncorhynchus gorbuscha (Walbaum, 1792) (Salmonidae), in the Sea of Japan in 1980–2023
    Authors: T.A. Shatilina, G.S. Tsitsiashvili, M.A. Osipova, T.V. Radchenkova
    Year: 2024
    Source: Russian Journal of Marine Biology

  • Title: Determination of Stability and Reliability of Shortest Paths in a Graph through Lists of Labels in Dijkstra’s Algorithm
    Authors: G.S. Tsitsiashvili
    Year: 2024
    Source: Reliability: Theory and Applications

  • Title: Networks Based on Graphs of Transient Intensities and Product Theorems in Their Modelling
    Authors: G.S. Tsitsiashvili
    Year: 2024
    Source: Computation

  • Title: Algorithms for Approximating a Function Based on Inaccurate Observations
    Authors: G.S. Tsitsiashvili, M.A. Osipova
    Year: 2024
    Source: Reliability: Theory and Applications

  • Title: Limit Cycles of Length Two in the Rikker Model and Their Application in Fishing
    Authors: G.S. Tsitsiashvili, T.A. Shatilina, M.A. Osipova, T.V. Radchenkova
    Year: 2024
    Citations: 1
    Source: Reliability: Theory and Applications

  • Title: Controlled Queuing Systems with a Stationary Uniform Distribution
    Authors: G.S. Tsitsiashvili, Y.N. Kharchenko
    Year: 2024
    Source: Vestnik Tomskogo Gosudarstvennogo Universiteta – Upravlenie, Vychislitel’naya Tekhnika i Informatika

  • Title: Graph Algorithms for Calculating the Distribution of the Amur Tiger Tracks in Primorsky Krai
    Authors: G.S. Tsitsiashvili, V. Bocharnikov, S.M. Krasnopeyev, M.A. Osipova
    Year: 2024
    Source: Theoretical and Applied Ecology

  • Title: Statistical Evaluation of Input Flow Intensity in the Presence of an Interfering Parameter
    Authors: G.S. Tsitsiashvili
    Year: 2024
    Source: Conference Paper (No source information available)

  • Title: Formation of Large Anomalies in the Thermal Conditions of Waters on the Western and Eastern Shelf of the Sakhalin Island
    Authors: T.A. Shatilina, V.V. Moroz, G.S. Tsitsiashvili, T.V. Radchenkova
    Year: 2024
    Source: Physical Oceanography

  • Title: Fast Method for Estimating the Parameters of Partial Differential Equations from Inaccurate Observations
    Authors: G.S. Tsitsiashvili, A.I. Gudimenko, M.A. Osipova
    Year: 2023
    Source: Mathematics (Open Access)

 

Zengjing Chen | Probability Theory | Best Researcher Award

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Prof. Zengjing Chen | Probability Theory | Best Researcher Award

Shandong China at School of Mathematics Shandong University, China

Professor Zengjing Chen is a distinguished scholar in applied mathematics, financial mathematics, and probability theory, currently serving at Shandong University. With a Ph.D. in Applied Mathematics from Shandong University, his academic journey includes visiting positions at leading institutions such as INRIA (France), the University of Western Ontario (Canada), and the University of Rochester (USA). He has made significant contributions to nonlinear expectations, stochastic processes, and financial mathematics, reflected in his extensive publication record in high-impact journals like Econometrica, Annals of Probability, and Journal of Economic Theory. His leadership roles include chairing committees in the Society for Industrial and Applied Mathematics of China and the Bernoulli Society. A recipient of prestigious awards such as the National Natural Science Award and the Society for Industrial and Applied Mathematics of China Fellowship, Professor Chen’s research has advanced the theoretical foundations of risk analysis, asset pricing, and stochastic control, earning him global recognition in mathematical finance and probability.

Professional Profile 

Scopus Profile

Education

Professor Zengjing Chen earned his Ph.D. in Applied Mathematics from Shandong University, where he developed a strong foundation in probability theory and financial mathematics. His academic journey included postdoctoral research and visiting scholar positions at renowned institutions, such as INRIA in France, the University of Western Ontario in Canada, and the University of Rochester in the United States. These international experiences enriched his expertise in stochastic processes, nonlinear expectations, and risk analysis. Throughout his education, he was mentored by leading mathematicians, contributing to his profound theoretical insights and innovative approaches to financial mathematics. His Ph.D. research laid the groundwork for his later contributions to nonlinear probability and robust financial modeling. By combining mathematical rigor with practical financial applications, he has become a prominent figure in applied probability and mathematical finance, influencing both theoretical advancements and real-world financial decision-making through his interdisciplinary research.

Professional Experience

Professor Chen has held key academic and research positions throughout his career, primarily at Shandong University, where he has been a professor and mentor to numerous doctoral students. His professional experience extends beyond China, having served as a visiting professor and research collaborator at leading institutions worldwide, including INRIA in France, the University of Western Ontario in Canada, and the University of Rochester in the United States. As an active member of the global mathematical community, he has chaired committees in prestigious organizations such as the Society for Industrial and Applied Mathematics of China and the Bernoulli Society. His editorial roles in top-tier mathematical journals demonstrate his influence in shaping the direction of research in financial mathematics and probability theory. With a career spanning decades, his professional journey reflects a commitment to advancing mathematical sciences, mentoring young researchers, and fostering international collaborations that bridge theoretical research with practical applications.

Research Interest

Professor Chen’s research interests lie at the intersection of probability theory, financial mathematics, and stochastic processes. He has made pioneering contributions to nonlinear expectations, risk measures, and robust financial modeling. His work on sublinear expectations and G-expectation has significantly impacted mathematical finance, particularly in asset pricing, risk management, and stochastic control. He is also deeply involved in uncertainty quantification and the application of probability theory to economics, developing models that address market volatility and financial risk under uncertainty. His research extends to machine learning applications in financial mathematics, where he explores new methodologies for predictive modeling and risk assessment. By integrating advanced probability theory with financial applications, his work has provided critical insights into optimal decision-making under uncertainty. His studies have been widely published in leading mathematical and economic journals, influencing both academic research and practical financial strategies used in investment, banking, and insurance industries.

Awards and Honors

Throughout his career, Professor Chen has received numerous prestigious awards recognizing his contributions to mathematics and financial modeling. He was honored with the National Natural Science Award, one of China’s highest accolades for scientific research, for his groundbreaking work in nonlinear probability and financial mathematics. He is also a Fellow of the Society for Industrial and Applied Mathematics of China, a distinction awarded to scholars who have made significant contributions to applied mathematics. His research has been supported by major grants from the National Science Foundation of China, allowing him to lead influential projects in stochastic analysis and risk management. Additionally, he has been invited to deliver keynote lectures at major international awards, further solidifying his status as a leading expert in probability and financial mathematics. His accolades reflect his lasting impact on the field, inspiring a new generation of researchers and practitioners in mathematical finance and applied probability.

Conclusion

Professor Zengjing Chen stands as a globally recognized scholar in applied mathematics, probability theory, and financial mathematics, with profound contributions to nonlinear expectations and stochastic processes. His academic and professional journey has been marked by excellence in research, international collaboration, and mentorship. Through his pioneering work in robust risk modeling and uncertainty quantification, he has advanced theoretical frameworks that influence real-world financial decision-making. His recognition through prestigious awards and leadership roles in top mathematical societies underscores his impact on the field. As a researcher, educator, and thought leader, Professor Chen continues to shape the future of mathematical finance, probability theory, and interdisciplinary mathematical applications. His contributions remain fundamental to both theoretical advancements and practical implementations in risk management, asset pricing, and financial stability, ensuring his legacy as a leading figure in the global mathematical community.

Publications Top Noted

  • Title: Proof of a Conjecture About Parrondo’s Paradox for Two-Armed Slot Machines
    Authors: Huaijin Liang, Zengjing Chen
    Year: 2025
    Source: Advances in Applied Mathematics

  • Title: A Theoretical Model for a Vane with Stochastic Rotation
    Authors: Zengjing Chen, Xinwei Feng, Han Li, Shijie Xie
    Year: 2024
    Source: Physica D: Nonlinear Phenomena

  • Title: An Advanced Machine Learning Method for Simultaneous Breast Cancer Risk Prediction and Risk Ranking in Chinese Population: A Prospective Cohort and Modeling Study
    Authors: Liyuan Liu, Yong He, Chunyu Kao, Zengjing Chen, Zhigang Yu
    Year: 2024
    Source: Chinese Medical Journal

  • Title: A Quantum Technology for Reinforcement Learning on Channel Assignment
    Authors: Zengjing Chen, Lu Wang, Chengzhi Xing
    Year: 2024
    Source: Advanced Quantum Technologies

  • Title: Optimal Strategy for Bayesian Two-Armed Bandit Problem with an Arched Reward Function
    Authors: Zengjing Chen, Zhao Ang Zhang
    Year: 2024
    Source: Mathematical Control and Related Fields

  • Title: Approximate Optimality and the Risk/Reward Tradeoff Given Repeated Gambles
    Authors: Zengjing Chen, Larry G. Epstein, Guodong Zhang
    Year: 2024
    Source: Economic Theory

 

Shen Wang | Probability Theory | Best Researcher Award

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Dr. Shen Wang | Probability Theory | Best Researcher Award

Assistant professor at College of Science/Civil Aviation University of China, China

Dr. Shen Wang, an Assistant Professor at the Civil Aviation University of China, specializes in stochastic analysis, particularly in McKean-Vlasov Stochastic Differential Equations (SDEs) and invariant probability measures. He holds a Ph.D. from Tianjin University and has contributed to mathematical modeling through five SCI/Scopus-indexed journal publications and two patents. His research applies Wang’s Harnack inequality and the Banach fixed point theorem to establish weak well-posedness for SDEs with integrable drift. Dr. Wang has editorial appointments (2) and research collaborations (4), demonstrating academic engagement. However, with only one citation index, limited industry projects, and no professional memberships, his research impact remains in its early stages. Expanding his citation count, industry collaborations, and leadership roles in awards or professional organizations would further strengthen his profile. While he exhibits strong theoretical expertise, greater influence in applied research and broader academic recognition would enhance his suitability for prestigious awards like the Best Researcher Award in the future.

Professional Profile 

Scopus Profile

Education

Dr. Shen Wang earned his Ph.D. from Tianjin University, a leading institution recognized for its research in mathematics and applied sciences. His doctoral studies focused on stochastic analysis, particularly McKean-Vlasov Stochastic Differential Equations (SDEs) and their applications in probability theory and mathematical modeling. Through rigorous academic training, he developed expertise in advanced mathematical concepts, including Wang’s Harnack inequality and the Banach fixed point theorem. His education provided a strong foundation in both theoretical and applied aspects of stochastic processes, equipping him with the analytical tools necessary for high-impact research. His academic journey has been instrumental in shaping his current research directions, allowing him to contribute to the mathematical understanding of stochastic systems. With a commitment to continued learning, Dr. Wang actively engages with new methodologies and techniques that enhance his ability to address complex problems in stochastic modeling and probability theory.

Professional Experience

Dr. Shen Wang is currently an Assistant Professor at the Civil Aviation University of China, where he is involved in research and teaching in the field of stochastic analysis. His professional role includes mentoring students, conducting advanced mathematical research, and collaborating with fellow scholars on theoretical and applied probability studies. As an emerging researcher, he has undertaken one research project and has been actively contributing to the academic community through editorial roles in two journals and four research collaborations. While his current experience is primarily in academia, his work in stochastic differential equations and invariant probability measures has potential applications in finance, physics, and engineering. Expanding his research into interdisciplinary areas and industry partnerships would strengthen his professional impact. His teaching and mentoring efforts also help cultivate the next generation of mathematicians, reinforcing his role as an academic leader.

Research Interest

Dr. Wang’s primary research interests lie in stochastic analysis, probability theory, and mathematical modeling, with a focus on McKean-Vlasov Stochastic Differential Equations (SDEs) and their applications. His work involves investigating the well-posedness of these equations using Wang’s Harnack inequality and the Banach fixed point theorem to explore solutions under integrable drift conditions. His research extends to the existence and uniqueness of invariant probability measures for symmetric McKean-Vlasov SDEs and stochastic Hamiltonian systems. These mathematical frameworks are crucial in understanding probabilistic models in physics, finance, and engineering. While his contributions are largely theoretical, they have significant potential for real-world applications in areas such as stochastic control, machine learning, and optimization. To enhance his research impact, expanding into applied domains and increasing interdisciplinary collaborations with data scientists, economists, and engineers would be beneficial.

Awards and Honors

Dr. Wang’s contributions to stochastic analysis have led to notable academic achievements, including five SCI/Scopus-indexed journal publications and two patents related to his research. His editorial roles in peer-reviewed journals and four academic collaborations further highlight his growing influence in the mathematical community. While he has yet to receive major international recognitions, his work in stochastic differential equations positions him as a promising researcher. To strengthen his awards portfolio, Dr. Wang could pursue best paper awards, fellowships, and research grants, as well as increase engagement with international mathematical societies. His contributions to probability theory and differential equations indicate significant potential for future accolades in both theoretical and applied mathematics. Expanding his professional memberships and participating in prestigious awards would also enhance his recognition and increase his chances of receiving higher honors.

Conclusion

Dr. Shen Wang is an emerging researcher in stochastic analysis, with expertise in McKean-Vlasov SDEs, Wang’s Harnack inequality, and the Banach fixed point theorem. As an Assistant Professor at the Civil Aviation University of China, he has contributed to the field through five indexed journal publications, two patents, and multiple editorial and collaborative roles. However, with limited citations, industry engagement, and professional memberships, his research impact remains in the early stages. Strengthening his academic presence through interdisciplinary collaborations, industry partnerships, and leadership in professional organizations would further elevate his standing. While he is a promising candidate for future academic honors, additional efforts in expanding his research influence and citation impact are necessary to position him as a top contender for prestigious awards like the Best Researcher Award.

Publications Top Noted

Title: Weak Solution and Invariant Probability Measure for McKean-Vlasov SDEs with Integrable Drifts

Authors: Xing Huang, Shen Wang, Fenfen Yang

Year: 2024

Source: Journal of Mathematical Analysis and Applications