- C
Center for Solar-Terrestrial Research (CSTR)
Data Analysis Intern
- Developed Python data processing pipeline to analyze magnetometer measurements from 10+ geographically distributed stations in western Greenland generating 2K+ vector field plots visualizing magnetospheric behaviors
- Identified understudied convection patterns through comprehensive data analysis, discovering correlation between convection events and sudden density pressure variations in the magnetosphere
- Implemented 4th-order Butterworth low-pass filter with adaptive cutoff frequencies to isolate high-frequency magnetic variations, replacing interval-based methods that produced inconsistent cross-day comparisons
- Built an automated convection detection algorithm computing spatial and temporal gradients using curl analysis and Gaussian filtering with 80th percentile thresholding to identify significant rotation patterns in magnetic field data
- Designed and trained machine-learning models for image and mathematically-based detection of ionospheric convections
FEATURED PROJECTS
view moreL2 Order Book + TWAP Execution Engine
Built a limit order book engine in C++ with historical L2 replay and an adaptive TWAP execution.
The execution switches between IOC, passive, and skip decisions based on spread, imbalance, volatility, and a real time markout prediction model.
Backtested across 7 day replay data with completion tracking, cost decomposition, diagnostics, and Streamlit analysis dashboards.
C++
Python
NumPy
Pandas
Streamlit
Option Pricing and Risk Analysis
COMING SOON
Python