Summary
William Timkey is a computational linguist and PhD candidate at NYU with nine years of research and teaching experience exploring how humans acquire and process language using neural and statistical models. He has held research roles at Cornell and CMU investigating psycholinguistic phenomena and language under stress, and he brings practical data-science skills from teaching and mentoring at Harvard and Cornell. His work sits at the intersection of learnability, inductive biases, generalization, and representation learning, with a hands-on interest in probing black boxes—both brains and neural language models—for explanatory signals. He values rigorous quantitative methods and teaches foundational statistics to students across disciplines, reflecting a belief that statistical literacy is essential to good science. Based in New York, he combines strong programming and experimental design experience with a knack for translating complex model behavior into cognitive insights. An uncommon strength is his dual background in linguistics and computer science, enabling tight integration of theory-driven hypotheses with computational experimentation.
9 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Linguistics, Doctor of Philosophy - PhD, Linguistics at New York University
Bachelor of Arts - BA, Linguistics, 4.075, Bachelor of Arts - BA, Linguistics, 4.075 at Cornell University
Computer Science, 4.0, Computer Science, 4.0 at University at Buffalo