Zachary McCormick
(he/him/his)
My Research/Academic Interests
Fancy seeing you here! My name is Zach(ary) McCormick, and I am a first-year PhD student in the Cognitive Science program at Johns Hopkins University, advised by Dr. Margaret Renwick. I am broadly interested in the computational and neural mechanisms that support real-time language processing, with a particular focus on how listeners represent and infer phonological structure. I am especially curious to understand how the brain handles the complexities of spoken language—especially at the phonemic and prosodic levels—by drawing on probabilistic (e.g., Bayesian) models of cognition. This includes the study of how phonological and prosodic cues are used to navigate uncertainty in the speech signal, and how these cues are processed dynamically during comprehension. Through my work, I aim to employ methodological diversity in combining theoretical phonology with computational modeling to explore how abstract linguistic structures are grounded in perceptual and neural system, building, in the process, a more precise account of speech processing that reflects both its cognitive architecture and its real-time demands.
Fun Addenda
I'm also a lover of film/cinema, language learning (duh), travel, tennis, bowling, avoiding concision like the plague in all ways, and overusing phrases like "in all ways" :)
My Academic Path
My (postsecondary) academic path began at Purdue University (2021-2023), where I triple-majored in linguistics, Spanish, and Italian studies. My focus was largely on the P-side of linguistics, with special attention to Spanish-English bilingualism, Spanish phonetics, and the phonological patterns that emerge in contact settings. During this time, I gained early exposure to computational linguistics, though my interests remained grounded in human cognition and language use.
At Brandeis University (2023-2025), where I pursued my master’s in computational linguistics, I engaged more directly with technical work in automatic speech recognition (ASR) and text processing, while also engaging with neuroscience and cognitive science curricula and conducting preliminary research and literature reviews in visual cognition and auditory neuroscience. These experiences reaffirmed that my core interests lie not so much in building machine cognition, but in using computational tools to better understand the architecture and function of the human mind—particularly the neural computations underlying real-time language processing (i.e., how the brain predicts and interprets language as it unfolds over time).
This has all brought me to the Cognitive Science program at Johns Hopkins University!
