Professional Experience

Research Engineer
(Feb 2023 to Present)

Projects:

Collaborated across departments, using SolidWorks (GrabCAD Workbench for version control) for complex assembly,component design, BOM and prototyping (GD&T/DFMA); participated in weekly sprints, managing project milestones using Jiraand maintaining project documentation on Confluence
Collaborated cross-functionally to design electro-mechanical testing rigs for robotic CV applications, with Arduino-controlledsystems; performed subsystem bring-up, calibration and tuning
Improved efficiency of image data collection by 90% using Python-based automation scripts (OpenCV)
Created Python simulation tool for rapid validation of lighting subsystem designs – reduced iteration cycles from 2 days to 2h
Conceptualized modular in-house lighting solution (50% cheaper) using Python simulation tool, optimizing for thermal andelectrical management

Mobile Tethered Pelvic Assist Device (mTPAD) - used for gait correction in post stroke individuals and children with CP - by applying lateral and diagonal forces on the pelvis to alter the irregular gait of patients by changing their motor control patterns over repetitive tasks
Had some irregularities due to the reliance of the patients on the device's structure during therapy, reducing the intended rehabilitation effect of the force
Hence, proposed the addition of a Virtual Reality (VR) component to training with the mTPAD
Based on the popular technique of Exergaming (Exercise Gaming), designed a virtual environment which included a basic exergame of avoiding obstacles and projectiles with a simultaneous force being applied on the mTPAD
Directed to make the therapy session more engaging and quantifiable

Supervised team of 5 undergrad and grad students to devise alternative rover locomotion modalities to traverse lunar craters (with slopes > 35°) and lava tubes in extreme thermal and lunar terrain applications (and later, Mars)
Simulated and trained 16-parameter locomotion model on self-programmed physics simulator on Python (using VPython) by forming evolutionary algorithms to optimize gait and evolve gait-modulation for damage scenarios
Design, development, simulation on PyBullet and working demonstration of final proposed system to be done over next 2 phases for presentation in Nov 2022