Assistant Professor at Yibin University, China
Dr. Arash Sioofy Khoojine is an accomplished academic researcher specializing in applied statistics, complex networks, and financial time series analysis. With a Ph.D. in Statistics from Shanghai Jiaotong University and prior degrees in mathematical sciences from top institutions in China and Iran, he has developed a strong interdisciplinary foundation. His research focuses on statistical modeling of stock market turbulence, COVID-19 spread simulation using advanced SEIR models, and network-based predictive analytics, producing over a dozen peer-reviewed publications in high-impact journals such as Physica A, Entropy, IEEE Access, and European Physical Journal. He currently serves as an Assistant Professor at Yibin University in China, where he teaches econometrics and statistical applications in economics. Beyond academia, he contributes as a guest editor and reviewer for international journals and has authored a Springer book on pandemic modeling. Fluent in English, Persian, and Chinese, and skilled in multiple programming languages including R, Python, and C++, Dr. Khoojine exemplifies a globally engaged scholar whose work bridges theory with real-world applications in finance, health, and data science.
Professional Profile
🎓 Education of Arash Sioofy Khoojine
Dr. Arash Sioofy Khoojine possesses a rich and diverse academic background in mathematics and statistics, built across top institutions in Iran and China. He earned his Ph.D. in Statistics from Shanghai Jiaotong University (2015–2020), graduating with distinction (GPA: A), where he focused on statistical network analysis of financial markets. Prior to this, he completed his M.Sc. in Probability and Mathematical Statistics at Central China Normal University (2012–2015) with an impressive GPA of 93.2/100, ranking among the top students. His foundational studies began with a B.Sc. in Pure Mathematics from Tabriz Payame Noor University (2000–2005), preceded by a Pre-University Diploma in Mathematics from Taleghani Pre-University Center in Tabriz (1998–1999). This solid progression reflects his long-standing dedication to mathematical sciences and his pursuit of academic excellence across multiple cultural and academic environments.
💼 Professional Experience of Arash Sioofy Khoojine
Dr. Arash Sioofy Khoojine has built a multifaceted professional career spanning academia, research, and software development. Currently serving as an Assistant Professor at Yibin University in China since 2020, he teaches statistics, econometrics, and mathematical applications in economics while actively engaging in interdisciplinary research. His earlier academic roles include a Lecturer position at Xi’an International Studies University, where he taught applied statistics, and a Teaching Assistant post at Central China Normal University, supporting coursework in probability theory. Before transitioning to academia, Dr. Khoojine worked as a C++ Programmer at Hekmat Pajouh Tabriz Co. in Iran from 2007 to 2011, where he honed his computational and analytical skills. His journey also includes early mathematics tutoring in subjects like pre-algebra and linear algebra from 2004 to 2007. This diverse professional background highlights his ability to integrate theoretical knowledge with practical application, across both academic and technical environments.
🔬 Research Interests of Arash Sioofy Khoojine
Dr. Arash Sioofy Khoojine’s research interests lie at the intersection of applied statistics, complex networks, and computational modeling, with a strong emphasis on real-world applications in finance, economics, and public health. He is particularly focused on statistical network analysis, exploring the structural dynamics of financial markets during periods of turbulence. His work also delves into time series modeling, stochastic processes such as fractional Brownian motion, and hypothesis testing within theoretical statistics. Additionally, he has made significant contributions to the development of SEIR-based epidemic models for predicting the spread of infectious diseases like COVID-19. With expertise in statistical programming and simulation using tools like R, Python, and Monte Carlo methods, Dr. Khoojine continues to push the boundaries of data-driven insight in both academic and applied settings.
🏅 Awards and Honors of Arash Sioofy Khoojine
Dr. Arash Sioofy Khoojine has been recognized multiple times for his academic excellence and research potential throughout his career. Early on, he ranked among the top 5% of national entrance exam participants in Iran and secured the 40th position in the prestigious Pre-University Entrance Exam in Tabriz. During his undergraduate studies, he consistently achieved first-grade distinctions in advanced mathematics courses such as complex functions, hyperbolic geometry, and mathematical analysis. His exceptional performance continued during his postgraduate education, earning him the title of top-ranked student in his master’s program at Central China Normal University. As a Ph.D. scholar at Shanghai Jiaotong University, he was awarded a competitive scholarship worth 200,000 RMB, along with a research fund of 60,000 RMB to support his innovative work in statistical network analysis. These honors reflect Dr. Khoojine’s unwavering commitment to academic excellence and his impactful contributions to the field of mathematics and statistics.
🧾 Conclusion
Dr. Arash Sioofy Khoojine is highly suitable for the Best Academic Researcher Award. His academic journey is defined by interdisciplinary innovation, a strong international education, diverse research in critical areas like financial networks and public health, and prolific scholarly output. The blend of theoretical rigor and practical relevance in his work positions him as a standout candidate. His application reflects core values of academic excellence, international collaboration, and research relevance, all of which align well with the criteria for the Best Academic Researcher Award.
📚 Publications Top Noted
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Smart Farming Solutions: A User-Friendly GUI for Maize Tassel Estimation Using YOLO With Dynamic and Fixed Labelling, Featuring Video Support
- Authors: Ata Jahangir Moshayedi; Zhonghua Wang; Maryam Sharifdoust; Arash Sioofy Khoojine; Wei Zhang; Amin Kolahdooz; Jiandong Hu
- Year: 2025
- Citation: IEEE Access,
- DOI: 10.1109/ACCESS.2025.3554984
- Dynamic Anomaly Detection in the Chinese Energy Market During Financial Turbulence Using Ratio Mutual Information and Crude Oil Price Movements
- Authors: Lin Xiao; Arash Sioofy Khoojine
- Year: 2024
- Citation: Energies,
- DOI: 10.3390/en17235852
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Interconnectedness of Systemic Risk in the Chinese Economy: The Granger Causality and CISS Indicator Approach
- Authors: Omid Farkhondeh Rouz; Hossein Sohrabi Vafa; Arash Sioofy Khoojine; Sajjad Pashay Amiri
- Year: 2024
- Citation: Risk Management,
- DOI: 10.1057/s41283-024-00142-8
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Analyzing Volatility Patterns in the Chinese Stock Market Using Partial Mutual Information-Based Distances
- Authors: Arash Sioofy Khoojine; Ziyun Feng; Mahboubeh Shadabfar; Negar Sioofy Khoojine
- Year: 2023
- Citation: The European Physical Journal B,
- DOI: 10.1140/epjb/s10051-023-00628-6
- A State-of-the-Art Review of Probabilistic Portfolio Management for Future Stock Markets
- Authors: Longsheng Cheng; Mahboubeh Shadabfar; Arash Sioofy Khoojine
- Year: 2023
- Citation: Mathematics,
- DOI: 10.3390/math11051148