About Me

From construction sites to computational physics, exploring the intersection of discipline and innovation.

My Journey

My professional journey began in the most unexpected of places—construction sites and military service in the Korean Army. These experiences instilled in me a profound appreciation for discipline, precision, and systematic problem-solving. Working in construction taught me that complex problems require methodical approaches, attention to detail, and the ability to adapt when plans change. My military service reinforced these values while adding leadership, teamwork, and the importance of clear communication under pressure.

When I arrived at UC Santa Barbara to study Physics, I discovered that these foundational skills translated beautifully into scientific inquiry. The same systematic thinking that helped me navigate construction challenges now drives my approach to understanding the fundamental laws of the universe. Physics, with its elegant mathematical frameworks and rigorous experimental methods, became my new construction site—a place where I could build understanding from first principles.

As I delved deeper into computational physics, I began to see patterns that extended far beyond the laboratory. The mathematical models I used to simulate quantum systems, the statistical methods I applied to analyze experimental data, and the optimization algorithms I implemented for complex calculations—these tools felt remarkably similar to the analytical frameworks used in financial markets. This realization sparked my interest in quantitative finance, where I could apply the same rigorous analytical thinking to solve real-world economic problems.

My entrepreneurial experience placing 3rd in the New Venture Competition with "Masterminding" further solidified my belief in data-driven decision making. Leading a team to develop a startup concept taught me that successful ventures require not just innovative ideas, but systematic analysis, market research, and strategic planning—skills that directly translate to quantitative analysis and financial engineering. Today, I'm excited to bridge my physics background with quantitative finance, bringing the same precision and analytical rigor that served me well in construction, military service, and scientific research to the world of financial markets.

Currently Learning

Python, Linux, Machine Learning, Quantitative Finance

Interests

Computational Physics, Computer Vision, Quantitative Finance, Analog Lifestyle, Photography

Education

UC Santa Barbara - Physics (Junior)

Experience

Construction Work, Korean Army Service, New Venture Competition (3rd Place)

Documents & Credentials

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Resume

Latest resume with professional experience and education

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Curriculum Vitae

Comprehensive CV with academic achievements and research

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SAT Scores

Official SAT test scores and academic credentials

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Technical Skills

Programming & Scripting

Python (Advanced) Shell Scripting (Bash) Scientific MATLAB JavaScript LaTeX PostScript

Data Science & Python Ecosystem

NumPy/Pandas/SciPy Matplotlib (3D/Animation) PIL/Pillow (Image Processing) Tkinter (GUI) Sockets (TCP/IP) Multithreading

Quantitative & Numerical Analysis

Stochastic Modeling (Monte Carlo) Numerical Methods (PDE Solvers) Signal Processing (FFT/PSD) Statistical Analysis (Chi-Squared, p-value)

Engineering & Applied Tools

Linux/Unix (CLI) Git Raspberry Pi (GPIO/I2C) Data Engineering (Scraping, JSON) Hardware Integration Computer Vision (ImageJ)