Stuart T. Hamilton
Aerospace Engineering Portfolio
What lies behind us and|what lies before us are tiny matters|compared to what lies within us.
— Ralph Waldo Emerson
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ViewStudent-led team at Georgia Tech chasing the first hybrid rocket to take off and land vertically under its own power.
ViewA student-led team at Georgia Tech building the autonomous systems that fly a self-landing rocket. The goal is to be the first student group anywhere to take a hybrid rocket through vertical takeoff and landing, which puts guidance, propulsion and recovery on the same critical path.
Founded in 2023 to break the sound barrier with a fixed-wing UAV designed, built and flown entirely by students.
ViewFounded in October 2023 to break the sound barrier with a fixed-wing UAV designed and built by students. Vehicle programs span high-speed cruise through high-g loads, and the team is organised into five technical disciplines covering both the engineering and the logistics of getting an aircraft built, so knowledge transfers as members graduate.
Modelling sorbent behaviour for carbon capture, characterising how material structure drives capture performance and what limits it.
ViewDr. Seung Soon Jang's group in the School of Materials Science and Engineering. My work models sorbent behaviour for carbon capture, characterising how material structure drives capture performance and what limits it, through density functional theory and molecular dynamics simulations of material systems. A publication is expected by summer 2027.
Propulsion Systems Engineer · GT Propulsive LandersAug 2026 – Present
A kilonewton of hybrid fire...
The main engine for Monarch, a reusable hybrid lander. Nitrous oxide oxidiser burns against a cast paraffin grain at 40 barA chamber pressure, holding an average O/F of 7.1 across a 40 second burn. A short pre-combustion chamber addresses the partial combustion that liquefying fuels are prone to.
ViewParaffin cast into an ABS gyroid lattice at 10 percent infill. The lattice carries structural load the wax cannot, which keeps the grain intact under pressure and acceleration, and the open cell fraction is low enough that regression rate tracks a solid cast grain. It also makes the part straightforward to produce in house.
Paraffin · ABS gyroid · 10% infill
ViewA showerhead face that meters nitrous oxide into the chamber, with a dense orifice pattern and a central swirl element. Spray distribution sets how evenly the grain regresses, and a three centimetre pre-combustion volume sits behind it to anchor a stable flame before the flow reaches the fuel.
CEA · CFD · Hot-fire data
ViewThe main combustion chamber runs roughly 23 centimetres and is sized around a 40 barA operating pressure and a 40 second burn. The mixture is held slightly fuel rich at an average O/F of 7.1, which trades a little specific impulse for cooler wall temperatures and more margin on the ablative surfaces.
Chamber sizing · O/F sweeps · Thermal
ViewThrust is set by the oxidiser flow rate, so the feed system and its instrumentation are part of the engine. Chamber pressure, feed conditions and valve position are logged through every hot fire and compared with the predicted regression and O/F history, which is what a landing burn needs before it can be throttled.
Instrumentation · Data reduction · Hot fire
ViewOwner · Project Lead · Lead DeveloperOct 2024 – Present
The AI assistant of the future...
A desktop assistant that answers by consensus. Each question is put to a panel of more than 20 models, whose replies are weighted, fact-checked and reconciled into one response. It tracks the user's gaze, reads the screen and camera, and integrates with mail, calendar, Canvas, Spotify and CAD.
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ViewA calibration and inference pipeline built on MIT’s eye-tracking research that maps a webcam feed to a point on the display. Three guided poses establish the baseline, after which gaze serves as both a pointer and a context signal, allowing the assistant to resolve references to whatever the user is currently viewing.
Python · OpenCV · MIT gaze model
ViewCaptures the active display, isolates the region under the user’s gaze and converts it into structured context for the panel, whether that is a figure, a table, a plot or a page of coursework. The camera feed extends the same capability to the physical workspace, with a live link to Meta glasses planned.
Python · Computer vision · OCR
ViewThe layer that reduces twenty replies to one. Responses are weighted, contradictions are surfaced and resolved, claims are verified with sources and outliers are rejected. Model health, latency and rate-limit state are tracked continuously so that a degraded provider is removed from the vote automatically.
Java · Python · 25+ APIs
ViewA triage layer that assesses each request before committing resources to it. Simple queries are routed to a fast lightweight model while complex ones escalate to the full panel, keeping latency and cost proportional to the difficulty of the question.
Python · MATLAB · Java
ViewOwner · Project Lead · Lead DeveloperNov 2024 – Jul 2026
The whole market in one app...
A desktop workstation for quantitative finance research. Market data, filings, statistics, options analytics and backtests draw on one cached data layer, and an AI analyst reads the technical, fundamental and risk models together and reports where they disagree. A date-aware mode holds every tool to a chosen date.
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ViewAn autonomous search agent that works a topic rather than returning links. It navigates deep into sites, collects filings, reports and news, and cross-references what it finds until the fragments form one research picture. SEC filings can be queried directly, so an answer comes from the document instead of a summary of it.
Python · Web scraping · LLM agents
ViewReads company financials the way an analyst would: statements, earnings, margins, cash flow and returns on capital, broken out by business division where the reporting allows it. Discounted cash flows and bull, base and bear cases are built automatically, and live sentiment marks where price and fundamentals have separated.
Python · DCF modelling · Sentiment analysis
ViewThe statistical core of the platform. It computes return distributions, variance, percentiles and correlation, then extends into higher moments, conditional probability, volatility and the options Greeks. Portfolio risk comes back as beta, Sharpe, drawdown and value at risk. A strategy has to clear a backtest, a walk-forward test and a Monte Carlo run before it is used.
Python · NumPy · Monte Carlo
ViewSweeps thousands of securities across hundreds of technical, fundamental and quantitative criteria at once. Filters run on price and volume, on volatility and momentum, on gaps, and on expected movement weighted by how likely it is. A described market condition returns its matching names in seconds.
Python · SQLite · Parquet
ViewWork that is under way and not yet written up here. Each will be added once there is something to show beyond a description.
SolidWorks
CATIA
PTC Creo
Siemens NX
AutoCAD
Autodesk Inventor
Autodesk Fusion
Onshape
FreeCAD
Ansys
Abaqus
MSC Nastran
Patran
CFturbo
STAR-CCM+
OpenFOAM
Siemens Simcenter
OpenVSP
OpenRocket
RockSim
NASA CEA
Cantera
NPSS
FlightGear
MATLAB
Simulink
Python
C++
C#
C
Java
JavaScript
Html
Css
Lua
Rust
PowerShell
NumPy
SciPy
Pandas
Matplotlib
PyTorch
TensorFlow
Wolfram Language
Mathematica
LaTeX
Git
GitHub
Visual Studio
VS Code
IntelliJ IDEA
PyCharm
Eclipse
JupyterLab
LabVIEW
Multisim
STM32CubeIDE
Altium
LTspice
SQLite
Unity
Blender
OpenAI API
Anthropic API
Gemini APISolidWorksCATIAPTC CreoSiemens NXAutoCADAutodesk InventorAutodesk FusionOnshapeFreeCADAnsys MechanicalAnsys FluentAnsys WorkbenchAnsys MultiphysicsAnsys DiscoveryAnsys SpaceClaimAnsys ElectronicsAbaqusMSC NastranPatranCFturboSTAR-CCM+OpenFOAMSiemens SimcenterOpenVSPOpenRocketRockSimNASA CEACanteraNPSSFlightGearMATLABSimulinkPythonC++C#CJavaJavaScriptHtmlCssLuaRustPowerShellNumPySciPyPandasMatplotlibPyTorchTensorFlowWolfram LanguageMathematicaLaTeXGitGitHubVisual StudioVS CodeIntelliJ IDEAPyCharmEclipseJupyterLabLabVIEWMultisimSTM32CubeIDEAltiumLTspiceSQLiteUnityBlenderOpenAI APIAnthropic APIGemini API
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ViewMost of this work is the design and testing of propulsion hardware. Time on manual lathes, mills, and printers informs how a part is drawn, on the principle that a design should reach the shop already manufacturable rather than be corrected there. Modeling is carried out in SolidWorks, flow and thermal analysis in Flow Simulation, and structural analysis in Ansys. On the stand, I am responsible for instrumentation, data acquisition, and the Python behind both, since a test is only as useful as the record it produces.
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ViewCoursework in aerodynamics, structures, and control theory, plus reading past the syllabus. Results of consequence are checked by hand.
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ViewScheduling, purchasing, and documentation fall to me. Hardware is ordered to a sourced bill of materials, and the subsystems share one schedule.
B.S. Aerospace Engineering
Georgia Institute of TechnologyExpected May 2028
George Washington UniversityAug 2024 – May 2025
Coursework
A Summer 2027 internship in propulsion, test, or design engineering is the near-term objective. Most of that work is analysis, and the part I find most instructive is the point at which a prediction meets the hardware it was written for, since that is where the assumptions are either confirmed or shown to have been wrong. Over a longer horizon the intent is to carry systems from concept through qualification and flight.
Seeking a Summer 2027 internship · Eligible for security clearance
I am an aerospace engineering student at Georgia Tech, originally from Mechanicsburg, Pennsylvania. My interest in the field began with how things are built and why they fail, and most of what occupies me outside of class follows from the same question. A design can be correct on paper and still be wrong, so the work I value most is the work that is built and tested, where the result returns whether or not it is the one expected. Coursework and research supply what a project cannot reach on its own, and each is treated as a check on the other. Time away from the desk is spent biking, hiking, lifting, and drawing. What I look for in a team is a willingness to be wrong early, in front of a test stand or a colleague, rather than late and in front of a customer.
