Profiles
Orcid
📍Current Position
Graduate Student, University of Illinois Urbana-Champaign (UIUC)
Mingxi Li is currently pursuing a Master’s degree in Predictive Analytics and Risk Management at UIUC, United States. Since August 2023, Mingxi has been deepening his expertise in data-driven methodologies and predictive modeling, holding an impressive GPA of 3.89. His coursework has focused on cutting-edge subjects such as Artificial Intelligence, Statistical Learning, Advanced Predictive Analytics, and Applied Bayesian Analysis, which have provided him with a solid foundation in risk management and predictive analytics
📝Publication Achievements
Mingxi’s research work has already gained visibility through two significant publications. In 2024, he co-authored a study, “Predicting Body Composition in the U.S. Population Using Machine Learning Models,” published in Medicine & Science in Sports & Exercise. This work focuses on applying machine learning to predict body composition metrics, contributing valuable insights to health-related AI applications. Additionally, an upcoming article in the North American Journal of Economics and Finance titled “Regional FinTech Development and Total Factor Productivity Among Firms: Evidence from China” is set to be published in 2025. This paper examines the impact of FinTech development on productivity, reflecting Mingxi’s versatility in applying AI to diverse fields, including finance.
🔍Ongoing Research
Mingxi’s ongoing research projects center on leveraging machine learning and predictive analytics across various fields. His recent project on a Recommendation System for Amazon Products utilized an LDA-based recommendation model to improve collaborative filtering using NLP techniques. Another notable project involves Predictive Modeling in Flight Data, where he employed Random Forest algorithms to predict flight ground times with accuracy-enhancing methods such as feature engineering and performance evaluation.
Mingxi’s research interests are broad yet focused within predictive analytics, covering essential areas such as risk management, AI, and data science applications. His passion for bioinformatics, as evidenced by his machine learning model work in medical data, showcases his drive to explore interdisciplinary applications of AI, particularly in healthcare and finance.
🎓Academic Background
Mingxi graduated with a Bachelor’s degree in Finance from Southwest University of Political Science & Law, China, in 2022, where he maintained a solid GPA of 3.5. His finance education included a robust curriculum focused on Corporate Finance, Financial Supervision, Financial Risk Management, and Finance Engineering. His journey into predictive analytics at UIUC allows him to merge his financial knowledge with AI, making him uniquely qualified for data-intensive finance roles.
🏆Scholarships and Awards
Mingxi has shown exemplary academic performance, achieving a GPA of 3.89 in a rigorous program at UIUC. His dedication has not only earned him high grades but also contributed to several impactful projects in fields as varied as finance, health, and technology.
🧬Bioinformatics
Mingxi’s work on predictive models for heart disease reflects his engagement with bioinformatics, where he applied machine learning models, such as Random Forest and XGBoost, to identify key predictors of heart disease with an accuracy of 83%. This expertise emphasizes his interdisciplinary skillset and commitment to using data science to solve real-world health issues.
🌐Professional Associations
As part of his graduate journey, Mingxi actively engages in professional associations related to finance, data science, and risk management. These affiliations allow him to stay current on industry trends, collaborate with other professionals, and participate in discussions that shape his research and career path.
📚Training & Workshops
Mingxi has attended workshops focused on AI tools, machine learning, and data analytics, enhancing his technical expertise in Python, R, SQL, SPSS, MATLAB, and more. These sessions have equipped him with the skills needed to analyze and interpret complex datasets efficiently, preparing him for high-demand roles in the analytics field.
🎤Oral Presentations and🗣️Thought Leadership
Mingxi has presented his projects at academic and professional platforms, particularly those related to predictive modeling in health and finance. His ability to effectively communicate complex models and their implications for real-world applications demonstrates his readiness for roles that require both technical expertise and client-facing skills.
🧑🔬Tasks Completed as a Researcher
Mingxi’s portfolio includes various analytical projects with a strong research component, such as his work on Amazon’s Recommendation System and Flight Data Predictive Modeling. His ability to manage data processing, feature engineering, and model evaluation highlights his technical skills and attention to detail. Additionally, his role in developing predictive models for employee attrition and heart disease underlines his commitment to impactful, data-driven insights.
🚀Success Factors
Mingxi’s success stems from a unique combination of analytical acumen, technical skills, and a proactive attitude toward interdisciplinary research. His expertise in both finance and data science, combined with his practical experience in machine learning and predictive analytics, gives him a competitive edge. His participation in projects such as Amazon’s recommendation system exemplifies his adaptability and creativity in solving diverse problems.
🧪Publications & Laboratory Experience
Mingxi’s laboratory and data analysis experience are well-documented through his publications and projects. His exposure to various data-processing environments and use of analytical tools like Stata, SPSS, and SQL reflect a comprehensive skill set. His publication on body composition prediction and ongoing work in FinTech analytics attest to his research capabilities and laboratory expertise.
🔍 Conclusion
Mingxi Li stands out as a dynamic and versatile candidate with strengths in predictive analytics, risk management, and data science. His educational background, bolstered by hands-on experience in finance and machine learning, positions him as a valuable asset to any data-intensive field. Mingxi’s interdisciplinary knowledge, combined with his commitment to innovation, will likely lead him to make significant contributions to both academia and industry.
Publications