What our workshop is about
The driving forces of progress in NLP are the people behind the work. We learn from their work. But to generate such good work, what are the principles and strategies they used? What are the roadblocks, challenges, mistakes, and lessons learned? These are quite valuable to the newbies across different career stages. In fact, we always reach out to the senior people around us for advice and reflect on their stories when we start a new career chapter - (1) fresh phd students reach out to early career researchers including senior phds or recent graduate, (2) early career researchers reach out to mid/late career professors, (3) company newbies reach out to industrial leaders. But often, only a few people would be approachable around us. This workshop aims at making the sharing of successful researchers’ stories and lessons learned to be accessible to everyone in our community. Such sharing would be very inspiring and helpful for those who might be struggling with making a choice or feeling lost right now. Our workshop will line up with sessions dedicated to individual career stage groups; each session will consist of 3-5 speeches and a panel QA & discussion to interact with the audience.
Previous version
Our workshop will be similar to the SSLL Workshop at ICCV 2021. While many stories and lessons can be transferred from CV to NLP, we aim at a more specific NLP audience and advocate for NLP specific lessons and stories to help our community and students.
Organizers
Sherry Wu is an Assistant Professor in the Human-Computer Interaction Institute at Carnegie Mellon University Her research lies at the intersection of Human-Computer Interaction and Natural Language Processing, aiming to support humans interacting with imperfect AIs, by debugging and correcting AIs interactively.
Yuval Pinter is a Senior Lecturer in the Department of Computer Science at Ben-Gurion University of the Negev, focusing on NLP as PI of the MeLeL lab. Yuval got his PhD at the Georgia Tech of Interactive Computing as a Bloomberg Data Science Fellow, working on representations at the word level and below.
