12345678
12345678
ABCD
ABCD
Arjun Shah

Aerospace PhD candidate at Stanford. Uncertainty quantification for machine learning, applied to aircraft design.

looking for a Summer 2027 internship [email protected]GitHubResume
01

Chronos - desktop water tunnel

desktop water tunnel
airfoil section at incidenceflow conditionercalendar displayclick for details
02

Rear wheel adapter

load-bearing assembly
An FEA result on the redesigned adapter, coloured by stress, with the highest values at the fillets around the mounting holes.click for details
52%lighter, by CAD mass properties ECO-WHEEL-001
03

First-responder delivery drone

first responder payload
The quadrotor standing in grass at a flying field, carrying its payload mount and antenna, under an overcast sky.click for details
4 FLIGHTSautonomous, in test PERS-RESP-001
04

Tailsitter VTOL UAV

tailsitter VTOL
click for details
4 PROTOTYPESbuilt and flown AGL-TAIL-001

published work

  • 01GRUBS: Data efficient surrogate modeling via gradient and uncertainty driven adaptive samplingAIAA Aviation
  • 02Impact of technology maturation on advanced hydrogen fuel cell aircraftJournal of Aircraft
  • 03Uncertainty quantification of machine learning models with adaptive sampling applicationsAIAA SciTech
  • 04The critical plastocapillary number for a Newtonian liquid filament embedded into a viscoplastic fluidJournal of Non-Newtonian Fluid Mechanics
  • 05Fuel cells for single-aisle regional aircraft: system configuration, performance, and costInternational Journal of Hydrogen Energy
  • 06Modeling and characterization of a novel propulsion system for hydrogen fuel cell aircraftAIAA SciTech 2025
  • 07Multi-fidelity analysis and reduced-order modeling of wing-body aerodynamicsAIAA Aviation
drawnA. SHAH
subjectSELECTED WORK
sheet1 of 1
views4
date2026-10-10
rev7519D19