Leading the design and development of a deployable airbrakes system for the UMass Rocket Team’s next-generation competition vehicle. The system is designed to dynamically modulate aerodynamic drag during ascent to precisely control apogee — a crucial requirement for high-power rocketry competitions like NASA USLI and IREC, where scoring depends on proximity to target altitude. The project integrates mechanical design, aerodynamic simulation, and embedded control software into a robust and testable subsystem capable of surviving high-speed, high-vibration flight environments.

Project Goals & Achievements

• Full-System Design Integration: Spearheading development of an active drag-modulation system, including 3D-modeled aerodynamic surfaces, actuation mechanisms, sensor integration, and onboard control logic for real-time apogee targeting.

• Aerodynamic & Structural Analysis: Using SolidWorks, ANSYS FEA/CFD, and OpenRocket simulations to validate deployment loads, hinge stresses, and drag coefficients across Mach 0.6–0.9 flight regimes.

• Embedded Control Software: Programming microcontroller-based firmware (Arduino architecture) to read barometric and IMU sensor data, apply a PID-based feedback loop, and actuate servos for adaptive control during powered ascent.

• Testing & Validation: Prototyping and bench-testing the actuation system to evaluate torque margins, deployment timing, and mechanical resilience under vibration/shock testing conditions representative of flight.

• System Redundancy & Safety: Implementing fail-safe logic to prevent mid-flight malfunctions—ensuring full retraction on signal loss and mechanical locking to avoid partial deployment.

• Future Expansion: Planning to integrate telemetry feedback for real-time airbrake performance monitoring and post-flight data visualization—enabling iterative refinement and closed-loop optimization over successive launches.

Developing a custom modular launch vehicle with a 4-inch diameter and base length of 5.5 ft (expandable to 7 ft with experimental payload/booster module), designed to certify at the L2 level. The vehicle uses a rugged “Blue Tube” airframe and plywood fins/bulkheads, paired initially with an Aerotech J450 motor and a subsequent planned upgrade to a K535 class motor. Onboard avionics include a BlueRaven flight computer (with an EasyMini backup) mounted to a custom 3D-printed sled. Simulation and testing aim at an apogee of ~4,500 ft and a velocity near 827 ft/s. Future iterations will incorporate airbrakes, roll control surfaces, live telemetry, and custom flight computer integration. 

Project Goals & Achievements

• End-to-end system ownership: Designed, built, and integrated every subsystem—from structure and propulsion to electronics and recovery—demonstrating full lifecycle engineering.

• Modular growth architecture: Engineered the vehicle with expandable length and booster sections, enabling a flexible payload bay and re-use pathways for future advanced phases.

• Structural-engineering mindset: Selected Blue Tube airframe material for its high strength/weight performance and Mach-capability. Baltic birch plywood fins, centering rings, and bulkheads support load-bearing and durability under high stress.

• Simulation-driven design: Utilized CAD (SolidWorks/Onshape), OpenRocket simulations, and manufacturing processes (additive manufacturing, CNC, laser cutting) to optimize performance ahead of physical testing.

• Flight-ready preparation & validation: Gearing first launch for ~4,500 ft, ~827 ft/s, with ground tests (pop tests) and avionics validation scheduled — positioning the vehicle for certification and advanced flight regimes.

Designed and built a custom First-Person-View (FPV) quadcopter, integrating mechanical assembly, power management, and embedded control systems. The project combined electronic systems design with aerodynamic optimization and hands-on fabrication to create a stable, responsive flight platform for both recreational and experimental testing.

Project Goals & Achievements

• System Integration: Combined brushless motors, electronic speed controllers (ESCs), flight controller, and custom power distribution board into a compact and serviceable layout.

• Telemetry & Video Feedback: Integrated FPV camera and video transmitter with ground station display, allowing live visual feedback and flight data monitoring.

• Mechanical Design & Fabrication: Modeled frame geometry in SolidWorks, 3D-printed key components, and selected composite materials to minimize weight and vibration.

• Control & Flight Tuning: Configured PID control parameters using Betaflight and tuned response curves for stability, maneuverability, and signal latency optimization.

• Testing & Iteration: Conducted progressive flight testing to validate component reliability, battery endurance, and heat dissipation under various flight conditions.

As part of the HackUMass 2024 hackathon (university-wide competition at University of Massachusetts Amherst), teamed up to build WorkoutLlama — a web application designed to simplify workout planning and tracking for students overwhelmed with fitness goals. Users set preferences (experience level, available days, session time, fitness objectives), and the app generates a personalized workout schedule. They can log sets, reps, weights, and over time the system recommends adjusted future values based on progress.

Project Goals & Achievements

• Backend architecture & data logic: Developed the server-side logic to process user preferences, build personalized workout schedules, and dynamically update recommendations based on logged workout data.

• Dataset manipulation & algorithm development: Worked with external API datasets (exercise libraries, performance metrics) and created algorithms to select workouts, scale difficulty and adjust weight/rep goals week-to-week.

• Full-stack collaboration & rapid deployment: Partnered with front-end teammates (HTML/CSS/JavaScript, React) to deliver a minimal viable product within the hackathon timeframe; judges praised the UI and schedule algorithm despite not placing.

• User experience focus: Ensured the backend design enabled smooth user flows — login, schedule creation, workout logging, and recommendation updates — enhancing usability and adoption potential.

Created a Python-based software tool to optimize launch vehicle configurations by analyzing parachute types and mass distribution alternatives. Inputs include parachute inventory and vehicle mass configurations; outputs include descent velocity, landing kinetic energy, drift distance, and cost ranking. The software simulates performance of each configuration and ranks them to reduce manual workload of configuration screening.

Project Goals & Achievements

• Automated design decision support: Built a tool that saved the team over 20 man-hours of manual calculations by automating simulation of each configuration across multiple criteria (landing velocity, kinetic energy, drift, cost).

• Inventory-driven optimization: Mapped existing parachute inventory and module mass-distributions into the model, allowing reuse of components and rapid iteration of configuration trade-offs.

• Ranking of outcomes: Generated spreadsheets with recommended configurations and associated metrics, providing actionable insights to the team’s design and flight-preparation process.

• Reusable engineering tool: Positioned the software as a repeatable asset for the team, enabling faster design cycles and improved decision-making for recovery system selection.