some research

I am an undergraduate researcher working in Professor Chris Callison-Burch's lab. My research interests include applying deep learning techniques to natural language processing problems, specifically in the domain of black-box model evaluation, information extraction, and dialogue systems. I have publications in NAACL, ACL Anthology, and SPIE Defense.

You can find my Google Scholar profile here.



A scientific chatbot evaluation framework for automatic and human evaluation of dialogue. Published NAACL 2019.


Real or Fake Text?

Crowd-sourced gamification of evaluation for large-scale neural language models.


Predicting Orderliness Using Wikihow

Performing temporal event reasoning by fine-tuning BERT-based neural language models.


Deep DNA (CRISPR) Lineage Tree Reconstruction

A simulation framework for the zygote development process to achieve a dataset size required by deep learning models, and various supervised and unsupervised approaches for cell mutation tree reconstruction.



Leveraging cloud architectures to perform intelligence, surveillance, and reconnaissance. Published SPIE Defense 2016.


Evaluation Criteria for Human and Computer Written Text

Human-annotated taxonomy of both errors made by large-scale neural language models, and characteristics of human-written text.


GROVER: Generating Rap by Observing Verses

An LSTM-based with attention model written in PyTorch that uses the CMU pronounciation dictionary to generate rhyming lyrics with inflection and meter.