Skip to main content Jan 2025 - May 2025 Jan 2025 - May 2025 Scientific Computing Methods Portfolio Numerical methods coursework covering roots, interpolation, IEEE-754 tools and error analysis. Software ›
- Completed 8 computational math assignments: Taylor series, root-finding theory, polynomial interpolation, error analysis
- Implemented IEEE-754 converter in Python for 32/64-bit representations handling normalized, subnormal, infinities, NaN
- Built relative error bound calculator demonstrating machine epsilon and numerical precision in scientific computing
Mar 2025 - Mar 2025 Mar 2025 - Mar 2025 Root Analysis Visualizer Interactive root-finding analysis comparing Bisection, Newton, and Secant methods. Data ›
- Built Python Streamlit app comparing 3 numerical methods (Bisection, Newton's, Secant) for nonlinear equation solving
- Implemented convergence analysis with Matplotlib error plots, iteration tracking, and parameter sensitivity analysis
- Architected modular codebase with 4 Python modules (numerical_methods, test_functions, visualization, report)
Mar 2025 - Mar 2025 Mar 2025 - Mar 2025 Math374P3 Streamlit app for analyzing nonlinear root-finding algorithms Data ›
- Built modular Python toolkit for nonlinear root-finding using Bisection, Newton's, and Secant methods
- Created interactive Streamlit web app with configurable tolerances and real-time visualizations
- Integrated pseudocode explanations directly into the interface for educational clarity
Feb 2025 - Feb 2025 Feb 2025 - Feb 2025 Numerical Differentiation Methods Visualizer Streamlit tool analyzing forward vs central difference error behavior with truncation and rounding error plots. Data ›
- Developed Python Streamlit app analyzing numerical differentiation errors comparing forward and central difference methods
- Created interactive Matplotlib visualizations showing truncation vs rounding error across step sizes (10^-1 to 10^-16)
- Computed optimal step sizes and validated theoretical error bounds for IEEE-754 floating-point arithmetic