About Me
I am a statistician and data scientist with research interests in artificial intelligence, education, and quantitative analytics. My work focuses on developing interpretable and trustworthy AI methods that transform complex educational data and financial data into meaningful insights for research and decision making.
My recent projects explore large language models, educational data mining, curriculum-industry alignment, and statistical learning. I am also interested in applying machine learning and quantitative methods to financial markets, where large-scale data can be transformed into interpretable signals for investment research and decision support.
Beyond research, I enjoy building open-source research tools, developing reproducible data science workflows, and teaching students to think critically through statistics, programming, and artificial intelligence.
Academic Journey
My academic background combines financial engineering, statistics, and artificial intelligence. Throughout my studies and research, I have been interested in how quantitative methods can bridge theory and practice by solving meaningful real-world problems.
Over time, my interests naturally expanded from financial modeling toward educational data science and trustworthy AI. Today, my research brings together statistics, machine learning, and domain knowledge to build transparent and evidence-based intelligent systems for both education and quantitative applications.
Current Work
Currently, I am working on several interdisciplinary research projects involving educational analytics, large language models, and quantitative finance. My recent work includes AI-assisted curriculum-industry alignment, interpretable machine learning for teacher workforce research, and large language model applications in financial news analysis.
During Summer 2026, I serve as a STEAM Instructor at Kean University, where I teach research methods and quantitative methods while mentoring high school students in developing independent research projects.
Research Interests
My research interests include Artificial Intelligence, Machine Learning, Statistics, Educational Data Mining, Large Language Models, Learning Analytics, Financial Data Science, and Decision Intelligence.
“I believe the most valuable AI systems are those that not only produce accurate predictions, but also help people understand, trust, and act on data.”