About Me
Hi, I'm Rongzhi (Dennis). I am currently pursuing my Master of Data Science at Harvard University. My passion lies at the intersection of quantitative finance, predictive modeling, and strategic problem-solving. Beyond algorithms and data, I am also a content creator exploring lifestyle aesthetics through a data-driven lens.
Education & Experience
Harvard University
Master of Science in Data Science • Expected May 2027
Relevant Coursework: Machine Learning, Advanced Analytics of Finance.
University of Edinburgh
BSc (Hons) Mathematics and Statistics • GPA: 3.98 (Rank: 4th/83)
Sep 2021 - May 2025
Focused on Stochastic Processes, Bayesian Data Analysis, and Statistical Inference.
Research Assistant
University of Edinburgh • Edinburgh, UK
Sep 2024 - Sep 2025
Processed 1M+ essays using PySpark and conducted stylometric research to detect AI-generated writing using ML classifiers (SVM, Random Forests).
Algorithm Analyst Intern (Data Science)
Meituan Data Center • Shanghai, China
Jun 2024 - Sep 2024
Designed online A/B experiments for ranking strategies (achieving 12% CVR lift) and prototyped LLM-assisted multi-modal CTR features.
Publications
Stylometric Detection of AI-Generated Texts: Evidence from Human and Machine-Written Essays
Rongzhi Chen, Jingqi He, Shizhao Xiong, and Gordon J. Ross • 2022
This study adapts stylometric techniques to distinguish between human- and AI-generated texts across 110 subject areas. By evaluating classifiers like Burrows' Delta, Random Forest, and SVMs on a dataset of 4,346 essays, our findings reveal that AI-generated texts exhibit striking stylistic uniformity, while human writing is marked by variability and individuality.
Read Full PaperSelected Projects
Quantitative Investment & Risk Modeling
Modeled non-Gaussian tail risk using GARCH volatility forecasting and Value-at-Risk (VaR). Backtested Pairs Trading strategies utilizing Co-integration and Vector Autoregression to exploit mean-reversion signals.
Derivatives Pricing via Deep Surrogates
Engineered "Deep Surrogate" Neural Networks to approximate complex pricing functions, significantly accelerating computational efficiency compared to traditional Monte Carlo simulation baselines.
A/B Testing & Traffic Allocation Framework
Evaluated traffic allocation policies via randomized controlled experiments. Executed systematic model sweeps across logistic regression and gradient-boosted models, improving online CTR uplift while preserving downstream conversion stability.
Mindset & Philosophy
Deconstructing Systems,
Understanding Human Nature.
Beyond quantitative models and data pipelines, my deepest intellectual curiosity lies in sociology, philosophy, and the mechanics of human nature. I approach the world not just as a data scientist, but as a strategist navigating complex systems.
I thrive on critical thinking and rigorous debate. True strategic advantage comes from understanding the underlying logic of society and the psychological drivers of human behavior. I build my sovereignty through an extreme internal locus of control—owning my efforts, decoding failures, and constantly evolving.
"True sovereignty is not about building impenetrable armor, but having the courage to embrace vulnerability. It is about transforming the relentless drive of a 'lone wolf' into the empathetic vision of a leader who creates genuine value."