Building at the intersection of biomechanics, medical devices, and embedded systems. From smart insoles to haptic gloves — I engineer solutions that bridge the gap between clinical insight and physical hardware.
I'm a Mechanical Engineer pursuing my M.Eng. at UC San Diego, specializing in Medical Device Engineering. With a B.Tech. in Mechanical Engineering from MIT World Peace University (GPA: 3.98/4.0), I combine deep mechanical intuition with a passion for life-changing biomedical technology.
My work spans finite element analysis of orthopedic implants, biomechanical motion capture for Parkinson's patients, and full-stack wearable device development — from sensor fabrication to real-time data visualization.
I'm driven by a simple belief: the best medical devices feel invisible to patients while delivering precise, life-improving data to clinicians.
Engineered a wireless two-module haptic system: a spectacle-mounted sensing unit with a VL53L5CX Time-of-Flight sensor and BLE transmitter, and a forearm-mounted feedback module. Implemented multimodal haptic feedback using a Peltier thermoelectric actuator and VCA vibrotactile motor, with closed-loop thermal control (15–42 °C). Algorithms map obstacle distance/direction to thermal pulses and vibration cues within 0.3–3 m range.
Designed an 8 Fr cardiac ablation-style catheter with an elastic resin distal tip and Pebax braided shaft, integrating piezoresistive contact-force sensing. Developed real-time force estimation and haptic feedback using Arduino Nano 33 BLE and MATLAB. Achieved detectable sensing in the 0.05–0.5 N range with <50 ms feedback latency.
A bidirectional wearable haptic glove integrating FSRs, flex sensors, and an IMU for real-time hand motion tracking. Mapped position/motion into a Unity virtual environment with vibrotactile feedback for closed-loop force-proportional response. Achieved 65% motion translation and feedback efficiency.
A smart insole instrumented with custom-fabricated pressure sensors and an IMU on a flexible PCB. Captured plantar pressure distributions and foot orientation with real-time Processing visualization. Achieved 80% accuracy in foot orientation tracking versus dynamic walkways in clinical patient evaluations.
Open to research collaborations, internship opportunities, and conversations about medical devices, biomechanics, or wearable tech. Based in San Diego, CA.
alele@ucsd.edu