To measure critical cardiac parameters such as left ventricular output through the use of non-invasive methods such as electrodes in an effort to detect early onset heart disease.

Team Members:

Spencer Denton
Paul Han
Abinav Krishnan

An intuitive web-based exploration tool for students taking Computer Architecture and those who are also looking to learn how changing system parameters affects performance metrics.

Team Members:

Ben Endara
Tianfang Guo
Cordell Mazzetti
Jackson Schilling

The future of electric power in naval applications leans towards the utilization of DC power distribution given its prevalence in energy systems and power electronics. However, DC is extremely susceptible to faults. Our team designed a system that implements a converter to transform from a high voltage bus to power an arc fault detection circuit which relays the location of the fault to another device using WiFi. Solving this issue of arc faults in DC systems for electric ships will be impactful by encouraging corporations and agencies to implement DC electric power.

Privacy Policies serve as essential blueprints outlining how organizations handle user data. Yet, their lengthy nature and the use of complex language can pose challenges for users trying to fully grasp what they're agreeing to.  PrivacyCheck utilizes the power of Natural Language Processing Machine Learning models to summarize the complexities of privacy policies, score them on 10 user control questions and compare them to the standards of the European Union’s General Data Protection Regulations (GDPR).

The Sanctum healthcare data marketplace, is a centralized online hub where participants will be incentivized to provide medical data in exchange for compensation; this data can then be publicly purchased and used for various research and development purposes such as model-making. A particular healthcare domain that could benefit from a data marketplace like this is pathology.

Team Members: 

Saleh Ahmad
Mihir Ali
Umar Choudry
Helen Liu
Jacob Marquardt
Billy Nguyen

This project aims to quantify the risk and instability associated with a specific type of cryptocurrency called fiat-backed stablecoins. Our work is split into two subsytems - a simulation and a time-series ML model that predict a specific stablecoin's price. Through the web application, users can interact with the simulation in a virtual playground where they can manipulate risk parameters to see how the predicted prices change. Users can also toggle between different stablecoins to see the associated ML model output.

Electrifying transportation is a crucial step in meeting international goals to combat climate change. The EcoCAR EV Challenge brings together universities to compete in a 4-year long Advanced Vehicle Technology Competition sponsored by the DOE, GM, Mathworks, and many more. The UT team is challenged to upgrade a full electric 2023 Cadillac LYRIQ to improve its fuel economy, power, drivability, and autonomous driving features. The FH01 Senior Design Team has joined Year 2 the competition to help the UT team fully integrate new motors and controllers.