Software engineer on the Mission Autonomy team working on a wide range of fields including distributed teaming + tasking, sensor management, motion planning, and autonomous behavior development.

Developed and implemented optimization based solution for fitting lines and arcs to flight paths while respecting kinematic constraints in C++.

TA for MIT 16.405/6.141, a robotics capstone for Aerospace Engineering, and EECS Majors.- Created labs covering a breadth of robotics topics including: controls, perception and computer vision, localization, and path planning.- Covered both theoretical concepts and implementation using ROS.- Assisted in deploying virtual tools during transition to remote learning during Spring of 2020.

Robust Data Association for Object Level SLAM (Sep 2018 – Jun 2018)- Researched and implemented various image space descriptors in C++- Designed testing framework for comparing different descriptor methods for robust data association- Adapted and implemented DBoW2 for object association using features from bounding boxesFast Planning for Contact-Aware Manipulation Under Uncertainty (Jan – Aug 2018)- Determined failure modes and verified approximations for a combined feedback control and MDP algorithm- Designed and implemented tests in C++ for novel MDP merging algorithm- Analyzed performance of merged MDP algorithm and compared to baselines

Developed and implemented two Particle Swarm Optimization (PSO) based algorithms for finding multiple feasible routes between waypoints using MATLAB

- Analyzed failure patterns in the acoustic models used in voice recognition software using Audacity and Excel- Designed tests to characterize parameters for valid input signals for the Julius voice recognition platform- Created new acoustic models using Julius and HTK to make the speech recognition system more robust and suited for use with operational noise on the river