Skip to main content



Presentation Link:

Team Final Presentation Team Members Company/Customer Project

05/03, Monday, 

9:00 - 10:00 AM


Alexander Harms

Katelyn Lamison 

Tracy Le

Eric Mullen 

Renee Mei Jing Teoh

VT Industries, Inc.

This project would relate to the use of current production data to predict and optimize the production of fire rated doors. VT Industries would be the main user and this project would include features like predicting the mechanical properties of the product based on input parameters such as raw material quality, production temperatures, weather conditions etc. Successful completion of this project would lead to decreased scrap rate and increased throughput of our plant.


05/04, Tuesday, 

9:00 - 10:00 AM


Alejandro Delbrey 

Andrew Fahmy 

Noah Heasley 

Evelyn Shiqi Khew 

Jonathan Vetting

Dr. Stone Chen The goal of the project is to design a 3D biochemistry virtual lab environment, which can simulate actual experiments taught in the biochemistry lab course BBMB102. The software should be completely web browser based, can be accessed from the Internet by any computer, and has a “game” feeling—something like “Minecraft”.
SD3 05/04, Tuesday, 10:00 - 11:00 AM

Xin-Jun Loh 

Trevor Smith 

Riley Spick 

Kyle Vetsch 

Brendan-Wei-Yu Yeong

LT, Inc. There are all kinds of wearable devices that have the capability of collecting health data. Lean Techniques, in partnership with Boon Logic, is looking to capture heart rate data and use Boon Logic's anomaly detection to identify potential health problems in the end user wearing the device. This project will act as a proof of concept for a project with a major medical provider interested in the capabilities available in everyday wearables.

05/05, Wednesday, 

9:00 - 10:00 AM


Malik Bulur 

Tao Li

Timothy Schommer 

Carter Wunsch 

Junran Zhang

Vermeer Corp Deep learning models require extensive manual trial and error with expensive resources to find an optimal parameter set. Implement a genetic algorithm to automatically and systematically find optimal parameters & hyperparameters for deep learning convolutional neural networks. The objective is to build the smallest deep learning model with the highest accuracy.

05/05, Wednesday, 

11:00 AM - 12:00 PM


Luzhuo Chen 

Amrithaa Ilanchelian 

Huidong Luo 

Ashton Nelson 

Quinn Sturm

Dr. Simanta Mitra

There are a plethora of animation tools described in the computing literature. But, these tools are restricted to a particular domain or they have pre-defined algorithms that they can animate. Some examples include Git with d3, VisualGo, and Loupe etc. Most of these tools use JavaScript as their main background. The main goal of this project is to develop a general-purpose animation tool, which can be used to animate any general animation such as moving a car, blinking a star but also, support animations that run an internal algorithm such as Git, Data Structures or animating the working of an adder in computer architecture.