Integrated M.S.–Ph.D. Student · Industrial Engineering · Hanyang University
Financial Engineering Lab · Master's stage, second semester
Current Focus / Achievements / Research / Project Collection
I am a second-semester student in the integrated M.S.–Ph.D. program in Industrial Engineering at Hanyang University, affiliated with FINX Lab. I earned my bachelor’s degree in Industrial Engineering at Hanyang and joined FINX Lab as an undergraduate researcher before continuing my graduate studies in the same lab.
My research interests lie in financial machine learning, time series analysis, data generation, and LLM-based agents.
| Research / collaboration | Focus / role | Status |
|---|---|---|
| Stablecoins | Stablecoin research | Ongoing research |
| Data Generation | Data generation research | Ongoing research |
| Neural ELS Hedging | Neural network–based optimal control for ELS hedging | Ongoing collaboration |
| WorldQuant BRAIN | Research Consultant | Current role |
| Competition | Result / status |
|---|---|
| KDD Competition | 🏆 1st Place |
| Mirae Asset AI Festival | Participated · Results pending |
Applied LSTM and Transformer models to dynamically rank 19 commodity futures based on basis-momentum (BMOM), a hybrid factor combining momentum and term structure. Code
Integrated LSTM and GARCH models to jointly predict return and volatility of Bitcoin. Demonstrated improved forecasting accuracy under high volatility regimes. Code
Conducted a text mining analysis to quantify tone shifts in MD&A before and after Korea’s New External Audit Act. Used Difference-in-Differences methodology to show significant increases in abnormal tone post-reform, suggesting improved strategic language use and enhanced investor transparency.
Developed an LSTM-based sequence autoencoder to extract latent vectors from malicious Python code across 11 behavioral types. Trained a conditional GAN (CGAN) to generate malware-type-specific latent vectors, which were decoded back to source code using autoencoder decoders. Evaluated classification accuracy, reconstruction error, and semantic consistency of generated samples. Code
A collection of projects spanning quantitative finance, data science, experimental research, software, and interdisciplinary design. Expand each category to explore the projects.
Quantitative Finance & Data Science · 5 projects
Modern Portfolio Theory, CAPM and Factor Model, Closed-form BlackScholesMerton pricing model, Binomial tree Code / Code
Forecasted monthly air passenger volume using ARMA modeling. Evaluated forecasting accuracy and seasonality components.
Built a classification model using SVM to predict loan approval decisions based on borrower-level financial attributes from real-world P2P lending data. Code
Applied Random Forest and AdaBoost regression to predict used car market prices. Preprocessed real-world listings and evaluated performance using RMSE. Code
Explored the effect of discount factor (gamma) on Q-learning convergence when solving a maze. Analyzed exploration-exploitation tradeoffs using MATLAB; found minimal difference in convergence time on small maps. Code
Experimental & Interdisciplinary Research · 5 projects
Applied a 2⁷⁻³ fractional factorial DOE to analyze effects of phosphoric acid deoxidizer, neutralizer concentration/time, and adhesion promoters on aluminum bonding strength at –65°F. Identified significant factor interactions impacting low-temp peel strength.
Investigated microbial diversity changes in Korean fermented foods (cheonggukjang, jeotgal, kimchi) across fermentation periods using 16S rRNA sequencing via Ion Torrent and Ion Reporter pipelines. Results showed pH/salinity-driven shifts in microbiome structures. Code
Designed ion-exchange resins using plant-based cellulose to selectively absorb lithium ions from seawater. Compared Li absorption efficiency across different functional groups and bead formation conditions.
Designed a cross-step filtration system modeled after fish gill structures to capture fine dust in vehicle exhaust. Used SolidWorks and Flow Design to simulate fluid flow, and built a detachable .STL-based prototype optimized for safety and energy efficiency. Code
Developed a directional sound system using acoustic phase control. Applied MATLAB to optimize speaker array configurations and control signal origin with function generator input.
Software, Business & Project Design · 4 projects
Developed a solution to encourage coffee shops to participate in spent grounds collection through a subscription model and eco-friendly platform. The initiative aimed to raise public awareness of coffee waste as a recyclable resource.
Built generalized rock-paper-scissors game and a “catch-the-mouse” strategy game in Java as part of team assignments in object-oriented programming.
Proposed a digital literacy education service powered by ChatGPT. Designed curriculum frameworks targeting students and non-technical users. Code
Delivered a presentation on “Make Megaprojects More Modular”, discussing modularization benefits in large-scale engineering projects.
| Area | Technologies & methods |
|---|---|
| Programming | Python · R · SQL · C · C++ · Java · MATLAB |
| Machine Learning | PyTorch · TensorFlow · Keras · Scikit-learn · XGBoost · LSTM · GAN |
| Data & Statistical Analysis | Pandas · NumPy · STATA · MINITAB · GARCH · NLP · Time Series Forecasting |
| Development | Git · GitHub · Jupyter · VS Code · Anaconda · Docker |
Broader Interests & Background
Investment Science · Financial Engineering · Forecasting · Machine Learning · Data Mining · Optimization · Operations Research · Cybersecurity · Data Analytics · ADSP
- Hanyang University — Integrated M.S.–Ph.D. in Industrial Engineering
Currently enrolled · Master's stage - Hanyang University — Bachelor's degree in Industrial Engineering
Graduated
Financial Engineering · Machine Learning · Time Series · Data Generation