Jared Junkin is an Assistant Professor at Johns Hopkins University and a Machine Learning Researcher at a quantitative finance firm in New York City. Prior to his current job, he worked as a Machine Learning Research Engineer at the Johns Hopkins Applied Physics Laboratory. His research interests include tokenization methods, post-training techniques, and mechanistic interpretability. If you have a question about his research or are interested in taking one of his courses, please contact him at jjunkin2@jh.edu
Education History
- B.S, Computer Science, Duke University
- M.S, Electrical & Computer Engineering, Johns Hopkins University
Work Experience
Assistant Professor, Johns Hopkins University
Courses
Applied Machine Learning
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