Under the direction of Dr. Tom Goldstein in UMD’s machine learning capstone course, I am working on a project designed to test the effectiveness of large language models for hyper-targeted phishing...

As a part of undergraduate research with Dr. Sahil Shah, I am developing a spiking network for object detection. Currently, I am building and comparing several networks for object detection includ...

While at JHU APL, I developed a communication script between GPT 3.5 Turbo and Dolly 12B or Stable Vicuna 13B allowing them to engage in a directed dialog designed to eliminate manual testing of la...

I supported the development of a shift equivariant Vision Transformer. By making the vision transformer shift equivariant, it would potentially better classify images that are shifted from their or...

For my data science class’ final project, I chose to compare the performance of different deep learning architectures on the classic MNIST dataset. In the project, I used a convolutional neural net...

While at JHU APL, I created transformer-based machine learning model for anomalous network traffic detection that yielded significantly higher accuracy than previous LSTM-based models. I also depl...

I analyzed moral foundations from text using a BERT model while working at the Johns Hopkins Applied Physics Laboratory. The text was categorized into the six moral foundations as described here. ...

As a part of my second high school internship at the Johns Hopkins Applied Physics Laboratory, I expanded my previous LSTM-based anomalous network traffic model to detect additional types of traffi...

As a part of my first high school internship at the Johns Hopkins Applied Physics Laboratory, I developed LSTM-based machine learning models for anomalous network traffic detection. I also created ...