Portfolio

Developed an algorithmic trading strategy in Python using 50-day and 200-day moving average crossovers combined with an Average True Range (ATR) volatility filter to generate reliable buy/sell signals. Performed comprehensive backtesting on historical stock data, resulting in a 50% increase in profitability compared to traditional crossover methods.

Implemented rigorous risk management: Sharpe Ratio, Max Drawdown, and VaR metrics for capital markets–grade evaluation. Position sizing and stop-loss orders to minimize potential losses and improve risk-adjusted returns.

Built a Python model using Pandas, NumPy, and SciPy for optimizing a tech stock portfolio with Markowitz's Modern Portfolio Theory. Simulated 10,000 portfolios, calculated key financial metrics, and constructed the Efficient Frontier.

Achieved maximum Sharpe ratio of 1.04 with optimized allocation: 62.47% Google, 23.75% Tesla, and 13.77% Apple.

Industry-specific framework for market volatility analysis, applied to the Vanguard S&P 500 Index ETF (VFV). GARCH-based volatility modeling to identify high-risk periods and potential anomalies through volatility clusters, kurtosis, and custom risk scores. Translates complex time-series data into actionable risk insights.

Enhanced the GTZAN dataset through data augmentation and conducted detailed analysis of audio signals. Visualized signals in the time domain and examined frequency components using FFT. Utilized AlexNet as a feature extractor on spectrograms, then implemented a fully connected neural network for classification—translating raw data into strategic insights.

High-performance system design for real-time autonomous navigation. CNN based on NVIDIA's model in the Udacity simulator. Integrated OpenCV and YOLOv3 for accurate lane detection and object recognition—engineering robust decision-making with real-time performance metrics.

Conducted kinematic, force, and stability analyses to resolve shortcomings. Incorporated advanced linkage systems for enhanced range of motion and degrees of freedom. Introduced independent arm movement, adjustable shoulder width, and optional stabilization. Performed motion analysis using Newton-Raphson methods.

Designed an FDM 3D Printer targeting the hobbyist market—maximizing speed and efficiency while minimizing space and cost. With a team of four from UofT, created three candidate designs using SolidWorks, including part analysis and cost design reports.

Achieved 3:1 speed reduction in a right-angle gearbox with 90° input/output shafts without worm gears. Complex math and physics—kinematic analysis, torque calculations, and Six Sigma optimization. This rigor in quantitative design translates directly to derivatives pricing and structured products. Utilized SolidWorks with GD&T; design optimized for 3D printing with fabrication under 6 hours.

Designed a complete air-compressed piston engine from an aluminium block using isometric drawings. Utilized CNC milling, lathe, and drill press. Optimized center of gravity through design calculations. Completed assembly in under two days.

For St. Lawrence College: designed a bracelet to assist an 8-year-old with ADHD by monitoring volume levels. SolidWorks structure design, Arduino microcontroller for voice detection and alerts. Rapid prototyping and 3D printing achieved a functional classroom-ready device.

Engineered a high-performance RC Aircraft from lightweight Styrofoam with Brushless Motors, ESC, Servo Motors, and Flysky FS-i6X transmitter (1.5 mile range). Integrated Flaps Landing, Fail Switch, and Auto Landing for enhanced safety and functionality.

Developed a Laser Security System for doors using Arduino UNO, breadboard circuits, and IR sensors. Merged circuit design with sensor integration for a responsive security solution.