Tanay T
- Research Program Mentor
PhD candidate at Stanford University
Expertise
aerospace engineering, mechanical design & simulation, sensors, signal processing, machine learning
Bio
Tanay develops AI-based modeling techniques for estimating the state and health of complex physical systems by leveraging multi-sensory data. With the main focus on UAVs, his research goal is to develop bio-inspired distributed sensing systems that bring nervous system-level situational awareness to human-made systems. Prior to working on AI-based models, Tanay developed computational and statistical models for designing application-specific multi-sensory devices. Tanay enjoys trying out new sports to a degree that made switching sports became a hobby for him. In his free time, Tanay also flies drones, experiments with alternative recipes, and critiques Formula 1.Project ideas
What attributes make a good airplane?
There are hundreds of distinct airplane types that currently fly in the air. Have you thought of why they all look different from each other? In this project, we study the design choices that aerospace engineers make to build safe, environmentally friendly, and performant airplanes. Then, we will come up with the best airplane design for a flight objective that we will select.
How good is your aircraft?
Manufacturing aircraft is very expensive. Thus, aerospace engineers iterate through many design alternatives during the development stage before finally deciding on the final model. In this project, we first investigate experimental (such as wind tunnel tests) and computational (such as fluid dynamics simulations) methods to determine aircraft performance metrics. In the second part, we analyze publicly available wind tunnel and/or simulation data of an aircraft to judge its performance.
