Nidhi Sonwalkar

Computer-Human Interface Engineer for Lunar Gateway’s Habitation and Logistics Outpost Module

Developed attitude/rate control algorithms and software framework in Simulink for Space Domain Awareness simulator reaction wheels and thrusters

• Collaborated on team to design deployers for light sails with shape-memory alloy frames tested on the International Space Station August 2025 • Designed and implemented PID controller and dynamics models for hard drive disk reaction wheel using Simulink, MATLAB, and C++ to control deployer spin rate • Conducted astronaut disturbance and spin up/down tests on deployer prototype using air hockey table

• Worked on IRAD team to develop updated Avionics architecture of Cygnus for future commercial space stations • Developed capabilities and CDH interface models in Cameo Systems Modeler using SysML for trade study analysis • Researched 25+ Flight Computer options for RAD 750 replacement trade study • Developed 200+ CDH requirements from CRS2 mission to inform updated Avionics architecture trade studies including Data Bus Architecture, Fault Tolerant Computing, and Flight Computer options

• Researched efficacy of various controllers for flexible space robotic models such as PID control, second-order structural filters, autonomous sinusoidal trajectory, and whiplash in Simulink • Developed equations of motion, mass matrices, and stiffness matrices for robotic models

• Collaborated on project team of 40+ members to design a semi-autonomous Mars Rover for University Rover Challenge 2024 • Designed and 3D printed mini arm with positional feedback servo motors to serve as a controller for modeling and teleoperating 6 degree-of-freedom robotic arm on rover using Autodesk Inventor CAD Modelling Software • Redesigned and tested prototype robotic arm and testing rig for inverse kinematics algorithm • Designed pan-tilt-zoom camera mount on deployable camera system for steady video feed of arm end effector • Tested rover’s electrical, software, and mechanical integration for the extreme retrieval and delivery mission

• Selected as a 2023 Brooke Owens Fellow • Worked on development and analysis of Commercial Destination Free Flyer (CDFF) space station • Designed and implemented MATLAB toolbox to store and apply visiting vehicle and space station input data and mission requirements to automate selection of best configurations for traffic model development and mission operations support • Implemented toolbox functions for power, thermal, and flight dynamics subsystems to provide output data for further design analysis including frontal area, solar torque, drag torque, inertial properties, and delta v functions • Assisted with management and closeout of Design Analysis Cycle using Agile workflow and Jira • Collaborated with Requirements and Verification team (RV&I) to develop functional decomposition model for human life support requirements • Revised and linked space segment and interface requirements to CONOPS using Rational Dynamic Object Oriented Requirements System (DOORS)

• Won 1st place for research paper and presentation titled “Cislunar Explorers Redesign: Multiple, Independent Technology Demonstrations Reduce Mission Risk” at AIAA Region 1 Student Conference and selected to present at AIAA Science and Technology Forum and Exposition • Collaborated on research team to develop a CubeSat to test novel water electrolysis propulsion, optical navigation, and symbiotic COTS technologies • Led Integration and Testing subteam to redesign electronics box, Propulsion system, ACS system, and 12U BUS • Performed analysis of the alternatives and fault tree analysis for CubeSat redesign • Developed CAD model of satellite structural mounts in SolidWorks CAD Modelling Software • Performed thermal analysis of propulsion system in ANSYS Simulation Software to determine thermal heating requirements • Assembled FlatSat, Electronics Box, and EDU for satellite testing including camera mounts, ACS system, harnessing and soldering, and separation and release mechanism

• Worked on research case study to evaluate potential of machine learning to improve VIIRS SO2 detection on the Suomi NPP and NOAA-20 satellites • Implemented machine learning models including Neural Networks, Logistic Regression, and Decision Tree Classifier in Python with over 90% accuracy in machine learning predictions against pre-existing data • Developed toolbox architecture to integrate machine learning applications with NASA’s data processing tools

• Researched, analyzed, and developed software to enable a fully autonomous system on the VIIRS and OMPS tools of the Suomi NPP and NOAA-20 satellites for processing of volcanic SO2, aerosol, and ash data and imagery for NASA’s Disasters Program and aviation management • Implemented and tested script changes to the VIIRS and OMPS tools to reduce operational costs, improve latency, add error logging, and expedite processing time

MS Aero Astro Student

Major: Mechanical Engineering, Minors: Aerospace Engineering and Robotics Awards/Achievements: John McMullen Dean's Scholar, Dean's List, Walter Werring Excellence Studies in Mechanical and Aerospace Engineering, Engineering Peer Advisor Outstanding Service Award

Summer Project at MIT Beaver Works Summer Institute Awards/Achievements: 1st place team for final CubeSat project and presentation