Anissa Neal

As a Ph.D. candidate in Linguistics at the University of Massachusetts Amherst, I have developed a strong background in designing, collecting, and analyzing data using quantitative, statistical, and machine learning approaches. My research experience spans over five years, with a focus on human comprehension of ambiguous and complex input. I have successfully led the development of 10+ experimental research projects, collecting data from 1000+ participants and analyzing it through statistical analyses in Python and R.

I have also demonstrated expertise in linguistics and computational modeling, utilizing PyTorch, TensorFlow/Keras, and HuggingFace Libraries to develop and present joint work on the ability of LLMs to comprehend different dialects. My research has been recognized with two competitive grants totaling $120,000 from the National Science Foundation.

Throughout my academic and research career, I have honed my skills in data analysis, statistical modeling, and programming languages such as Python, R, and SQL. I am confident in my ability to collect, clean, and statistically analyze data to produce comprehensive qualitative and quantitative reports.