Ryan Naderi

Implemented a stochastic Euler–Maruyama solver in Python to simulate the dynamics of a burnt-bridge ratchet molecular motor under diffusion Extended the model to two dimensions and analyzed collective motion and spring-coupled interactions between multiple motors Analyzed simulation results using trajectory statistics, mean-squared displacement, and other quantitative metrics to evaluate model behaviour and performance.

Computational Modelling (Volunteer) - Emberly Research Group, SFU - Vancouver, British Columbia

(2026-01)

• Implemented a stochastic Euler–Maruyama solver in Python to simulate the dynamics of a burnt-bridge ratchet molecular motor under diffusion
• Extended the model to two dimensions and analyzed collective motion and spring-coupled interactions between multiple motors
• Analyzed simulation results using trajectory statistics, mean-squared displacement, and other quantitative metrics to evaluate model behaviour and performance.

Undergraduate Laboratory & Experimental Analysis - Vancouver, British Columbia

(2022)

• Conducted experimental analysis of mechanical, optical, and electrical systems including harmonic motion, lens systems, wave behaviour, and RLC circuits to evaluate system response
• Applied statistical and process analysis methods including uncertainty quantification, regression, and least-squares fitting to assess data quality and improve measurement reliability
• Used Excel for statistical analysis, uncertainty propagation, and regression-based modelling of experimental datasets, including trendline fitting and error analysis
• Documented experimental workflows, results, and conclusions in structured reports with emphasis on clarity, reproducibility, and data-driven interpretation

Applied Physics - Simon Fraser University (2027-09)