Jason Eisner

The following is interview is from a series featuring faculty involved in natural language processing education. Johns Hopkins University Professor of Computer Science Jason Eisner chatted with us about courses he’s taught, which include Natural Language Processing (601.465/665) and Machine Learning: Linguistic and Sequence Modeling (601.765). Jason was previously interviewed by JHU’s Center for Educational Resources in February 2012 about teaching, and he’s also posted his “Statement of Teaching Accomplishments and Goals” on his webpage. He won JHU’s Robert B. Pond, Sr. Excellence in Teaching Award in 2005 and Alumni Association Excellence in Teaching Award in 2013. …


Emily M. Bender

As the next installment in our series on NLP pedagogy, we interviewed University of Washington Linguistics Professor Emily M. Bender. She has taught many courses and seminars in the past two decades, including Introduction to Syntax for Computational Linguistics (Ling 566), Introduction to Computational Linguistics (Ling/CSE 472), and Knowledge Engineering for NLP (Ling 567) multiple times. Emily is also Faculty Director of the Computational Linguistics Master’s program and an Adjunct Professor in Computer Science and Engineering. She is a passionate advocate for the use of linguistics in NLP, having authored the book Linguistic Fundamentals for Natural Language Processing: 100 Essentials…


(The following is the second in a series of interviews with natural language processing faculty on how they teach their courses.)

Lucy and I sat down with Yejin Choi, Professor of Paul G. Allen School of Computer Science & Engineering at the University of Washington and recent winner of the Borg Early Career Award. Her research interests include language grounding, commonsense knowledge, natural language generation, conversational AI, and AI for social good. She is also an adjunct professor of Linguistics, affiliate of the Center for Statistics and Social Sciences, and a senior research manager at the Allen Institute for Artificial…


(This interview is part of a series of interviews on the pedagogy of NLP)

The first interview in our series is with Dan Jurafsky, Professor of Linguistics and Computer Science at Stanford University, whose research resides at the intersection of NLP, linguistics, and social sciences. Dan was a fitting starting point for this blog series because Lucy’s journey in NLP began when she was a sophomore in his class, CS 124/LING 180: From Languages to Information. This course acts as the entry to a suite of upper-level classes: CS 224N (NLP with deep learning), 224W (social networks), 224U (natural language…


Natural Language Processing is truly an interdisciplinary field, combining elements of Linguistics, Computer Science, Statistics, and more. In the classroom, NLP educators choose which aspects to teach based on multiple constraints such as class length, student experience, recent advancements, program focus, and even personal interest. As a result, two NLP courses can look very different in terms of their content — despite teaching the same field. NLP courses often serve as students first introduction to the field and so the content can have a significant impact on the path these future scholars take and what is judged to be important…


Or, how to have a good research meeting with your advisor

This summer I’ve had the good fortune to work with a large group of 13 new undergraduate researchers in my lab. They are talented Michigan students who want to learn how to do world-class research but are just getting started along the path. One aspect of learning to do good research is learning how to do research with others — and in particular, when starting out, how to do research with an advisor. I wanted to touch on one small part of this process: meetings with an advisor. Meetings are a critical part of the knowledge transfer process but not…

David Jurgens

David Jurgens is an Assistant Professor in the School of Information at the University of Michigan

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