Seeking full-time aerospace roles · May 2027

PURDUE AAE · PROPULSION · COMPUTATION · SYSTEMS

Building aerospace systems through propulsion, computation, and systems engineering.

I’m an Aeronautical and Astronautical Engineering student at Purdue with hands-on experience in propulsion analysis, CFD, systems engineering, mechanical design, and computational research.

See selected projects Open résumé

01 / PROPULSION SYSTEMS 02 / COMPUTATIONAL ENGINEERING 03 / SYSTEMS & REQUIREMENTS 04 / TECHNICAL RESEARCH

SELECTED PROJECTS

Engineering work across propulsion, systems, and research.

Each project shows a different part of how I work: defining the problem, building the analysis or design, making tradeoffs, and checking the result.

01SPACE FORCE RESEARCH / MATLAB / BIBLIOMETRICS

Emerging Aerospace Technology Assessment

Conducted Space Force-funded research at the Air Force Institute of Technology using computational and bibliometric methods to support aerospace and defense technology assessment. My work focused on research-data processing, MATLAB-based analysis, and quantitative comparison of technical trends in areas including Applied AI and Scaled Hypersonics.

Space Force-funded researchApplied AI + Scaled HypersonicsMATLAB analysis

Project overview

During a summer research internship at the Air Force Institute of Technology, I worked within a six-intern team on a Space Force-funded research effort. I developed and used computational methods to organize research data, compare technology development, and support technical assessment across aerospace and defense topics, including Applied AI and Scaled Hypersonics.

My contribution included MATLAB-based data processing and quantitative analysis of bibliometric information, followed by interpretation of the resulting trends for engineering research questions. The project strengthened my ability to work with large technical datasets and turn them into structured, reviewable analysis.

Some details of the research are intentionally omitted from this public portfolio. The description here is limited to my role, general methods, and transferable engineering skills.

RoleSpace Force research intern working within a six-intern technical research team.

My contributionDeveloped MATLAB-based workflows for research-data processing, quantitative comparison, and technical trend analysis.

Engineering valueBuilt experience translating large research datasets into structured evidence that could support technical assessment and engineering judgment.

ToolsMATLAB, Python, Scopus, Excel, and local analysis tools.

02PROPULSION / FLUID SYSTEMS / CFD

Pressure-Fed LOX / Methane Feed System

Designed a pressure-fed LOX / methane feed system for a 1 kN liquid rocket engine. I built a Python analytical model to size the feedlines and injector flow areas, calculate pressure losses and tank-pressure requirements, then used CAD and ANSYS Fluent to check the feedline flow predictions.

1 kN thrust target0.363 kg/s total propellant flow35 bar tank pressure

FEED SYSTEM / CAD Overall CAD model of the pressure-fed LOX and methane feed system

Project overview

I started with a 1 kN engine requirement at 20 bar chamber pressure and an O/F ratio of 3.4. The analytical model calculated a total propellant flow of about 0.363 kg/s, split into 0.2673 kg/s LOX and 0.0955 kg/s methane. I then sized the feedlines, valves, and equivalent injector flow areas while tracking friction and component pressure losses.

The final baseline used an 8 mm LOX line and a 6 mm methane line. The model predicted required tank pressures of about 26.05 bar for LOX and 26.78 bar for methane, leaving roughly 9 bar and 8 bar of margin respectively from the 35 bar tank-pressure assumption. I also ran sensitivity studies on feedline diameter, tank pressure, and injector pressure drop to see which design choices had the largest effect.

For the CFD portion, I modelled the feedlines in ANSYS Fluent using the analytical mass-flow rates and cryogenic fluid properties. The goal was not to make the CFD unnecessarily complex; it was to check whether the 1-D model was giving reasonable feedline results. The Fluent cases converged and the analytical and CFD flow predictions were verified to be close, giving me a useful cross-check between the two methods.

Baseline design8 mm LOX line, 6 mm CH₄ line, 35 bar tanks, and 25% of chamber pressure allocated across the injector.

Flow sizing0.2673 kg/s LOX and 0.0955 kg/s CH₄, with equivalent injector diameters of about 3.79 mm and 2.90 mm.

Pressure marginRequired tank pressures were approximately 26.05 bar LOX and 26.78 bar CH₄, both below the 35 bar baseline.

ToolsPython, CAD / ANSYS Discovery, ANSYS Meshing, and ANSYS Fluent.

Feed-system design and CFD results

Overall CAD architecture of the LOX and methane feed system — Overall LOX / CH₄ feed-system CAD model

ANSYS Fluent static-pressure contour for the 8 mm LOX feedline — LOX feedline static-pressure contour

ANSYS Fluent velocity contour for the 8 mm LOX feedline — LOX feedline velocity contour

ANSYS Fluent static-pressure contour for the 6 mm methane feedline — Methane feedline static-pressure contour

Comparison of analytical feedline model and ANSYS Fluent CFD results — Analytical model vs. CFD validation

03MECHANICAL DESIGN / DOCKING / HYDROGEN

Forever-Flying Hydrogen Drone Docking System

Contributed to NASA’s University Student Research Challenge Forever-Flying Drones project by developing the docking and latching architecture for an autonomous offshore hydrogen refueling station.

NASA-funded research≈3.6 kN docking design load1 kg latch-mass limit2250 psi H₂ system context

FINAL DOCKING SYSTEM Final docking system for the Forever-Flying hydrogen drone project

Project overview

This multidisciplinary group research project was part of NASA’s University Student Research Challenge Forever-Flying Drones effort. The larger concept centered on hydrogen-powered drones that could autonomously dock at offshore stations, receive fuel generated from seawater, and return to operation with minimal human intervention in a high-pressure hydrogen system with a 2250 psi design context.

My primary responsibility was the docking and latching subsystem. I researched multiple docking concepts, compared latching approaches, developed the mechanical architecture for soft capture and hard restraint, and evaluated components such as push locks, bushings, actuators, and sensors. I also helped translate the system sequence into a practical docking workflow from approach and alignment through engagement, refueling, release, and undocking.

The project gave me experience working within a larger aerospace system where mechanical design, hydrogen safety, alignment tolerance, manufacturability, and autonomous operation all influenced one another. It strengthened my ability to make subsystem decisions that support the broader mission rather than optimizing a component in isolation.

Why I pursued itI wanted experience contributing to a real aerospace research project where several engineering disciplines had to work together toward one operational goal.

My contributionLed work on docking concepts, the latching mechanism, force and load reasoning, component trade studies, and integration of the latch into the overall docking sequence.

Engineering challengesThe design had to accommodate landing error, restrain the drone during fueling, support automated engagement, remain lightweight, and avoid interference with critical drone hardware.

What I learnedThe strongest component is not always the best solution; subsystem design requires balancing load capacity, alignment tolerance, simplicity, manufacturability, and integration.

Docking architecture and design decisions

Autonomous docking and refueling process workflow — Docking and refueling process

Selected push-lock latching concept — Selected push-lock concept

Bushing and alignment feature for the docking system — Alignment and bushing detail

Trade study comparing latching alternatives — Latching trade study

04MBSE / REQUIREMENTS / AI-ASSISTED ENGINEERING

AI-Assisted Systems Engineering — Landing Gear

Developed an Excel-based workflow that used Python and locally hosted language models to support requirement analysis, functional decomposition, verification planning, and preliminary failure-mode assessment for an aerospace landing-gear case study.

30 atomic requirements analysed9 INCOSE quality criteria18 preliminary FMEA entries

WORKFLOW / SOLUTION ARCHITECTURE Architecture of the AI-assisted systems engineering workflow

Project overview

During my internship at BlueKei Solutions, I developed and evaluated an AI-assisted systems-engineering workflow using an aerospace landing-gear mission as the case study. The goal was not to automate engineering judgement, but to reduce repetitive documentation work and give engineers a more structured starting point for review.

The workflow began with source requirements in Excel and used Python-connected local language models to break compound statements into atomic requirements, identify ambiguity, propose clearer wording, extract core functions, outline functional chains, and generate acceptance and verification criteria. I also organised the outputs into an INCOSE-style quality assessment covering necessity, appropriateness, clarity, completeness, singularity, feasibility, verifiability, correctness, and conformance.

I then extended the workflow into verification planning and preliminary risk analysis. Requirements were assigned proposed verification methods, criticality and cost levels, with suggestions for combining related verification activities. A preliminary FMEA connected functions and requirements to failure modes, effects, causes, controls, detection ratings, risk-priority numbers, and mitigation ideas. The project gave me a practical understanding of how requirements, functions, verification, and risk remain connected throughout a system lifecycle.

Why I pursued it I wanted to understand how AI could support real engineering workflows while learning systems engineering beyond what could be communicated in a standard résumé bullet.

My contribution Built the Excel and Python workflow, structured the model outputs, tested local LLM approaches, and developed the requirement, verification, and FMEA deliverables.

Engineering value The workflow created traceable starting points for requirement review, functional reasoning, verification planning, and risk identification while keeping human validation central.

What I learned AI outputs can accelerate early analysis, but their usefulness depends on structured inputs, repeatable evaluation, traceability, and careful engineering review.

Workflow and engineering outputs

Solution architecture for the AI-assisted engineering workflow — Solution architecture

Requirement analysis and refinement output — Requirement analysis and refinement

Verification planning output — Verification planning

Preliminary failure mode and effects analysis — Preliminary FMEA and risk prioritisation

05HIGH-POWER ROCKETRY / FLIGHT / SIMULATION

Tripoli Level 1 Rocket — LOC IV

Assembled and launched a LOC IV high-power rocket on an AeroTech H100W motor, earning my Tripoli Level 1 certification at ThunderStruck 2024. I also used OpenRocket to compare motor choices, wind sensitivity, stability, and recovery behavior before flight.

Tripoli L1 certifiedH100W flight motorThunderStruck 2024 certification flight

THUNDERSTRUCK 2024 / LOC IV LOC IV high-power rocket at ThunderStruck 2024

Project overview

I assembled the LOC IV kit, prepared it for flight, and successfully launched it on an H100W motor to earn my Tripoli Level 1 certification. Before the flight, I used OpenRocket to compare other compatible motors and examine how wind conditions, stability, altitude, and flight performance changed between cases.

Why I did it The project gave me a practical way to connect flight mechanics and simulation with real launch preparation, hardware, and recovery decisions.

What I did Assembled the kit, prepared the rocket for launch, flew it on an H100W motor, and completed the Tripoli certification process.

Further analysis Modelled the rocket in OpenRocket and compared motor choices and calm, moderate, and stronger-wind simulations.

What I learned OpenRocket made the tradeoffs between motor choice, wind, stability, and recovery timing visible before launch, while the certification flight reinforced the importance of accurate configuration data and careful launch preparation.

Photos, simulation results, and launch video

Tripoli Level 1 certification launch

LOC IV model created in OpenRocket — OpenRocket model

Simulated altitude profiles for different rocket motors — Motor comparison

Simulated landing drift under different wind conditions — Wind sensitivity

EXPERIENCE

Research and engineering experience beyond the classroom.

My work so far has included technical research, aerospace system design, model-based systems engineering, and undergraduate teaching.

SUMMER 2026

DEFENCE RESEARCH

Air Force Institute of Technology

Space Force-funded technical research involving bibliometric analysis, research-data processing, computational methods, and emerging-technology assessment.

2025—2026

AEROSPACE RESEARCH

Hydrogen Drone Docking & Refuelling

Mechanical and systems design for autonomous docking of a high-pressure hydrogen aircraft platform under operational loading and interface constraints.

SUMMER 2025

MBSE INTERNSHIP

BlueKei Solutions

Requirements, functional architecture, verification planning, automation, and failure analysis for reusable launch-vehicle landing-gear systems.

2024—2025

TEACHING EXPERIENCE

Purdue Physics Undergraduate Teaching Assistant

Supported students in introductory mechanics and electricity-and-magnetism courses through problem solving, laboratory guidance, and technical explanation.

ABOUT ME

I’m drawn to aerospace problems that connect analysis with real design decisions.

I grew up and completed my schooling in India before moving to the United States on my own to study aerospace engineering at Purdue.

That transition pushed me to become comfortable adapting quickly, taking on unfamiliar problems, and actively looking for opportunities beyond the classroom. Technically, my main interests are liquid rocket propulsion, hypersonics, and reusable launch systems. I enjoy work that lets me move between equations, code, CAD, simulation, testing, and system-level tradeoffs rather than treating them as separate activities.

Outside of project work, I also enjoy aerospace outreach and volunteering. I have volunteered through Purdue Space Day and at the AIAA K–12 booth during the Dayton Air Show, where I had the chance to help introduce younger students to aerospace and engineering.

Analysis

Fluid mechanics, propulsion, pressure-loss modelling, controls, data interpretation

Tools

MATLAB, Simulink, Python, ANSYS Fluent, CAD, Excel automation, Capella

Systems

Requirements, functional architecture, V&V planning, FMEA, trade studies

Communication

Technical reports, research presentations, workflow visualisation, engineering documentation

AVAILABLE BEGINNING MAY 2027

FULL-TIME OPPORTUNITIES

Looking to contribute to a team solving difficult aerospace problems.

I’m seeking full-time aerospace engineering roles beginning after my May 2027 graduation, with particular interest in propulsion, fluids, simulation, systems engineering, and related analysis work.

Email me ↗ LinkedIn ↗

GitHub coming soon

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