Phelps Family University Fellows Endowment

Njeri's project examined algorithmic fairness in resource allocation by comparing synthetic scholarship allocation models with real-world mortgage lending data. Using Python, machine learning, and established fairness metrics, she evaluated how predictive models can produce different outcomes across demographic groups, even when sensitive attributes such as race and sex were excluded from the training process.

Overview of PTE's Structure and Capabilities

This project's goal was the development a PostgreSQL Testing Environment (PTE). The PTE is an application that helps students iterate on their code by supplying automated feedback. It uses Gradescope's software as an API for all student and teacher interaction. It was developed specifically for PostgreSQL, an industry standard Relational Database Management System used in SLU's Database Systems and Security course. 

The aim of this project was to identify, write formulae for and write proofs for patterns in reversed digit pairs of numbers (e.g. 3482 and 2843).  My main accomplishments were: 

During this fellowship, there was work done with AI and Penetration testing tools to harden software and defend against cyberattacks. The testing site used was a website created in a Web Programming Class. Using Kali Linux software, which is used for penetration testing and digital forensics, a variety of tools were used to identify whether a site is encrypted or unencrypted, which also indicates whether a site is secure or not. These tools include Hydra, skipfish, burp suite, Wireshark and XSSer.

During the St. Lawrence Summer Fellowship, Cooper A. focused on addressing the challenges faced by sound editors and designers due to the lack of standardized organization in large audio databases. The project involved curating a dataset of over 77,000 audio files, totaling 151 hours, from various sound editors, including his father’s work. Using machine learning frameworks like TensorFlow and PyTorch, the project developed deep learning models and audio spectrogram transformers to categorize different sound effects.

The fundamental theorem of algebra states that every polynomial equation with complex coefficients has complex roots. These roots can be mapped on the complex plane, resulting in beautiful, geometric patterns called algebraic starscapes. I developed python code to compute and graph the complex eigenvalues of specific families of matrices, utilizing St. Lawrence's supercomputer for the millions of computations this required. I experimented with matrix size and integer inputs, as well as a multitude of variables in the graphic generation phase.

Drones are uncrewed vehicles that operate under the direction of software running on a “flight computer” – a computer that controls the drone as it travels along a pre-programmed path. This research dealt with  increasing the resiliency of the drone in the face of computer failures. We developed a method for transplanting certain sensor data from one flight computer to another, allowing a backup computer to take over the job of the flight computer while the problem is fixed.

My research project this summer aimed at determining the sequence of different peroxides present in membranipora RNA samples. By the means of using a transcriptome, a hypothetical DNA sequence of the different peroxides was theorized. By using the theoretical sequence, primers were made and used to perform an RT-PCR. The obtained DNA was inserted into a plasmid vector and cloned. The cloning process allowed DNA sequencing to be carried out. After this process, the actual DNA sequence of peroxidase mRNA was determined.

Camera quality on smart phones has been improving rapidly along with facial recognition technology. Photo and video editing apps have become increasingly popular and sophisticated. As people use these apps for entertainment, this has also raised concerns about how fake but realistic looking videos may sow confusion, uncertainty, and doubt about the veracity of images. These manipulated videos and other digital representation produced by artificial intelligence are called “deepfake”.