Careers in NLP Panel

Name: Careers in NLP, a panel in the Industry Track of NAACL HLT 2021

Time: Tuesday June 8 at 1pm PDT, 4pm EDT.

Duration: 60 minutes

The questions are based on the survey results from this form. Additional questions will be taken from the audience if time permits.

Moderator

Philip Resnik

Philip Resnik is Professor of Linguistics at the University of Maryland, with a joint appointment at UMD’s Institute for Advanced Computer Studies and an affiliate appointment in CS. He was named an ACL Fellow in 2020. He earned his Ph.D. at the University of Pennsylvania in 1993, and joined the University of Maryland faculty in 1996. Philip’s industry experience prior to entering academia includes time at BBN, IBM T.J. Watson Research Center, and Sun Microsystems Laboratories. Alongside academia he has been a technical co-founder for CodeRyte (NLP for electronic health records, acquired by 3M in 2012), and an advisor to Converseon (social strategy and analytics), FiscalNote (machine learning and analytics for government relations), and SoloSegment (web site search and content optimization). He was recently appointed to the Scientific and Technical Advisory Board of the Coleridge Initiative, a non-profit working with governments to ensure that data are more effectively used for public decision-making. His current work focuses on computational social science, NLP for mental health, and the cognitive computational neuroscience of language.

Panelists

Isabelle Augenstein

Isabelle Augenstein is an associate professor at the University of Copenhagen, Department of Computer Science, where she heads the Copenhagen Natural Language Understanding research group as well as the Natural Language Processing section. She also co-heads the research team at CheckStep Ltd, a content moderation start-up. Her main research interests are fact checking, low-resource learning and explainability.

Mona Diab

Mona Diab is a researcher at Facebook AI and a professor at George Washington Unviersity. She conducts research in Statistical Natural Language Processing (NLP) is a rapidly growing, exciting field of research in artificial intelligence and computer science. Interdisciplinarity is inherent to NLP, drawing on the fields of computer algorithms, software engineering, statistics, machine learning, linguistics, pragmatics, information technology, etc. In NLP, researchers model language and its use, and build both analytical models and predictive ones. In Professor Diab’s NLP lab, they address problems in social media processing, building robust enabling technologies such as syntactic and semantic processing tools for written texts in different languages, information extraction tools for large data, multilingual processing, machine translation, and computational sociolinguistic processing. Professor Diab has a special interest in Arabic NLP, where the emphasis has been on investigating Arabic dialect processing where there are very few available automated resources.

Jimmy Lin

Jimmy Lin is a Professor and the David R. Cheriton Chair in the David R. Cheriton School of Computer Science at the University of Waterloo. Previously, he was at the University of Maryland. He completed my Ph.D. in Electrical Engineering and Computer Science at MIT in 2004. From 2010-2012, He spent an extended sabbatical at Twitter working on services designed to identify relevant content to users (search, recommendation, etc.) and analytics infrastructure to support data science (Hadoop tools, machine learning libraries, etc.). He has also worked for Cloudera. His research aims to build tools that help users make sense of large amounts of data. He work at the intersection of information retrieval, natural language processing, and databases, with a focus on large-scale distributed algorithms and infrastructure for data analytics.

Sebastian Ruder

Sebastian Ruder is a research scientist in the Language team at DeepMind, London. He completed his PhD in Natural Language Processing and Deep Learning at the Insight Research Centre for Data Analytics, while working as a research scientist at Dublin-based text analytics startup AYLIEN. Previously, he studied Computational Linguistics at the University of Heidelberg, Germany and at Trinity College, Dublin. He is interested in transfer and multilingual learning and making ML and NLP more accessible.