• A Machine Learning Approach Towards Prediction of Pancreatic Cancer Using Gene Expression and DNA Methylation 

  Keller, Paige; Morehead, Samuel; Caterer, Zachary (2025-04)

  Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, accounting for over 90% of cases, and is characterized by aggressive growth, early metastasis, and resistance to therapy. A comprehensive ...

• Exploring Machine Learning Models : For IoT Network Intrusion Detection : A Literature Review and Comparative Analysis 

  Hagen, Jack; Strate, Ayden (2025-04)

  The Internet of Things (IoT) encompasses a variety of systems and devices that enable data exchange across networks. With this interleaved connectivity comes an inherent vulnerability to attacks. Traditional intrusion ...

• Program for Analysis of Filament Homogeneity in Bi2Sr2CaCu2O8-x (Bi-2212) and Nb3Sn superconducting wires 

  Coursin, Evan (2025-04)

  Superconductors are materials that can carry electricity without resistance at cryogenic temperatures, which is useful for large magnet applications such as particle accelerators. Bi2Sr2CaCu2O8-x (Bi-2212) is a superconductor ...

• Classifying Enzyme Substrates using Machine Learning 

  He, Kyle (2025-04)

  Knowing what types of enzymes a molecule will interact with can aid drug development by minimizing side effects due to unwanted interactions. In this project, we built and interpreted models for classifying enzyme substrates. ...

• Optimizing Math Department Scheduling 

  Bergeson, Brynn; McCallum, Katherine; Schwantes, Theodore (2025-04)

  Scheduling classes is a challenging and time-consuming task. The mathematical technique of linear programming has the potential to simplify this challenge by building a model of linear constraints to find the most optimal ...

View more