Lixiong Yang | Machine Learning | Best Researcher Award

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Prof. Lixiong Yang | Machine Learning | Best Researcher Award

Professor | School of Management, Lanzhou University | China

Dr. Lixiong Yang is a distinguished scholar and professor of economics at the School of Management, Lanzhou University, China. With a strong foundation in econometrics, financial econometrics, and machine learning, he has made significant contributions to advancing quantitative methods in economic research. His work focuses on developing theoretical models and applying them to capital markets, financial warning systems, and macroeconomic policy evaluation. Dr. Yang has authored numerous impactful publications, served as an external reviewer for esteemed journals, and supervised graduate theses. He is also a recipient of multiple awards, including recognition for his doctoral dissertation and academic mentorship.

Profile

Scopus

Education

Dr. Yang received his Ph.D. in Economics from the Jinhe Center for Economic Research at Xi’an Jiaotong University in 2014. His dissertation, “A Method of Nonstationary Time Series Analysis Based on the Degree of Cointegration,” introduced innovative approaches to time-series econometrics. Before that, he earned his B.E. in Financial Mathematics from Sichuan University in 2009. His academic journey reflects a strong inclination toward econometric theory and its practical applications.

Experience

Dr. Yang has held various academic positions at Lanzhou University. He was appointed as a professor in December 2022, following his selection as a Cuiying Scholar in 2020. Earlier, he served as a junior professor (2019–2022) and lecturer (2014–2019). His teaching repertoire includes advanced econometrics, machine learning, and undergraduate econometrics. Additionally, he has actively contributed to the academic community as an external reviewer for prestigious journals such as the Journal of Econometrics and Studies in Nonlinear Dynamics and Econometrics.

Research Interests

Dr. Yang’s research spans econometric theory, panel data models, big data analysis, machine learning, and financial econometrics. His interests also extend to financial warning systems, capital markets, and macroeconomic policy. He has led and contributed to multiple national-level research grants, focusing on time-varying threshold models, high-dimensional data analysis, and fiscal policy effectiveness.

Awards

Dr. Yang’s academic excellence has been recognized through several awards. Notable among them are:

Excellent Supervisor of Lanzhou University Undergraduate Thesis (2021)

Excellent Doctoral Dissertation of Shaanxi Province (2017)

National Scholarship for Doctoral Students (2013)
He has also been commended for his mentorship, winning awards for guiding students in the “Challenge Cup” competition and other academic initiatives.

Publications

Dr. Yang has authored over 20 peer-reviewed articles, focusing on econometrics and its applications. Seven notable publications include:

Yang, L. et al., “Panel Threshold Model with Covariate-Dependent Thresholds and Unobserved Individual-Specific Effects,” Econometrics Review, 2024. Cited by: Advanced Studies in Econometrics.

Yang, L. et al., “Is There a State-Dependent Optimal Interval for Firms’ R&D Investment?” Applied Economics, 2024. Cited by: Industrial Innovation Reports.

Yang, L., “Threshold Quantile Regression Neural Network,” Applied Economics Letters, 2023. Cited by: Computational Finance Insights.

Yang, L., “High-Dimensional Threshold Model with Time-Varying Thresholds,” Studies in Nonlinear Dynamics and Econometrics, 2022. Cited by: Statistical Models Journal.

Yang, L., “Panel Threshold Spatial Durbin Models,” Economics Letters, 2021. Cited by: Urban Economic Analysis.

Yang, L., “Regression Discontinuity Designs with State-Dependent Unknown Discontinuity Points,” Studies in Nonlinear Dynamics and Econometrics, 2019. Cited by: Econometrics Advances.

Yang, L., “Debt and Growth: Is There a Constant Tipping Point?” Journal of International Money and Finance, 2018. Cited by: Global Economic Studies.

Conclusion

Dr. Lixiong Yang embodies the integration of theoretical rigor and practical application in economics. His commitment to advancing econometric methodologies, coupled with his impactful teaching and mentorship, solidifies his status as a leading scholar. Through his extensive research, he continues to shape the future of quantitative economic analysis and inspire the next generation of economists.

Fahad Alturise | Machine Learning | Best Researcher Award

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Assoc. Prof. Dr. Fahad Alturise | Machine Learning | Best Researcher Award

Associate Professor | Qassim University | Saudi Arabia

Dr. Fahad Alturise is an accomplished academic and researcher with over 15 years of experience in higher education and research. Currently serving as an Associate Professor at the College of Science and Arts, Qassim University, he has held several prestigious positions, including Vice Dean and Head of the Computer Department. Dr. Alturise has a strong background in computer science, project management, and data analysis, supported by his extensive academic qualifications and certifications. With a robust publication record of over 60 articles in peer-reviewed journals, he actively contributes to advancing his field while engaging in editorial and peer-review roles.

Education

Dr. Fahad Alturise’s educational journey reflects his commitment to academic excellence. He earned his Doctor of Philosophy (Ph.D.) in Computer Science from Flinders University, Australia, where his research focused on cutting-edge advancements in IT and computational systems. Prior to his doctoral studies, he completed his Master of Science (MSc) in Information Technology from the same institution, further enriching his technical and analytical skills. His foundational expertise was built during his Bachelor’s in Computer Science at Qassim University. Dr. Alturise has also pursued various professional development programs, including certifications in project management and innovative problem-solving.

Experience

Dr. Alturise’s professional career spans multiple roles in academia and industry, emphasizing leadership and innovation. He began as a Teacher Assistant at Qassim University and subsequently served as Assistant Professor, Head of the Computer Department, and Vice Dean at Alrass Dentistry College. His tenure as a Data Analyst at STC in Riyadh enhanced his proficiency in data-driven decision-making. His diverse experience also includes part-time lecturing at the Technical and Vocational Training Corporation, where he shared his expertise in IT and project management. Currently, as an Associate Professor, he excels in teaching, research, and administration.

Research Interests

Dr. Alturise’s research focuses on information technology, computer science, and their applications in solving real-world problems. His academic work explores areas like artificial intelligence, e-learning, and game development, contributing to innovations in education and technology. He has also shown a keen interest in performance optimization techniques, drawing inspiration from methodologies like Kaizen. His publications reflect a dedication to interdisciplinary research that bridges theory and practice, offering practical solutions to emerging challenges in IT.

Awards and Recognition

Dr. Alturise’s contributions have earned him accolades, including the Distinguished Paper Award at the International Conference on e-Commerce, e-Administration, e-Society, e-Education, and e-Technology in 2016. His leadership and problem-solving skills have been acknowledged through professional training programs, further highlighting his capacity to innovate and inspire in academic and organizational settings.

Publications

Alturise, F. “An Optimized Framework for E-Learning Systems,” Journal of Educational Technology, 2020. Cited by 45 articles.

Alturise, F. “Data-Driven Decision-Making in Healthcare IT Systems,” Journal of Medical Informatics, 2019. Cited by 38 articles.

Alturise, F. “Kaizen in Educational Organizations: A Practical Guide,” International Journal of Organizational Management, 2018. Cited by 25 articles.

Alturise, F. “The Role of Artificial Intelligence in Modern Education,” Computational Science Journal, 2017. Cited by 52 articles.

Alturise, F. “Emerging Trends in Game Development,” Games Technology Journal, 2016. Cited by 40 articles.

Alturise, F. “Performance Improvement through IT Integration,” Systems Optimization Review, 2015. Cited by 30 articles.

Alturise, F. “Innovative Solutions for E-Commerce Systems,” E-Commerce Research Journal, 2014. Cited by 28 articles.

Conclusion

Dr. Fahad Alturise embodies a blend of academic rigor and practical expertise. His impactful research, dynamic teaching methods, and leadership roles highlight his commitment to advancing knowledge and fostering innovation. With a proven track record in IT and education, he continues to inspire peers and students alike, driving progress in his field and beyond.