Careers in Industry Panel
The NAACL 2018 Industry Track will provide students and job seekers a unique opportunity to meet some of the best NLP researchers and learn more about the range of careers from industry. The panelists, with experience in both industry and academia, will share their thoughts on topics related to industry careers of interest to the NLP community gathered via an earlier web survey. The topics include, careers in industry vs. academia, how to set research agenda in an industry setting, and others. We invite you to join our conversation which will offer the opportunity to ask the panelists questions and to network with some of the best NLP researchers with industry experience.
Philip Resnik (moderator): 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 received his BSc at Harvard in 1987, his Ph.D. in CIS at UPenn in 1993, and he joined the University of Maryland faculty in 1996. His industry experience prior to entering academia includes time at BBN, IBM T.J. Watson Research Center, and Sun Microsystems Laboratories. Philip was a technical co-founder of CodeRyte (clinical NLP), lead scientist for Converseon (spearheading development of their sentiment analysis platform, now marketed as ConveyAPI), and founder of React Labs (which took a crack at commercializing his research on scalable real-time response measurement and engagement using mobile devices). He is currently an advisor to Converseon and FiscalNote (government relationship management) and co-founder of a new startup,Thematically.
Jason Baldridge: Research scientist at Google in Mountain View, California, where he is focused on spatial language understanding and semantics. Prior to that he was an Associate Professor of Computational Linguistics at the University of Texas at Austin (2005-2016) and co-founder and Chief Scientist of People Pattern, an Austin startup working on social media analytics. Jason also consulted as a professor, including working with Philip Resnik to develop Converseon’s ConveyAPI sentiment analysis system. Jason received his Ph.D. from the University of Edinburgh in 2002, his masters degrees in both linguistics and computer science from UPenn in 1998 and his undergraduate degree anthropology from the University of Toledo, Ohio in 1996.
Laura Chiticariu: Chief Architect of IBM Watson Natural Language Understanding (NLU), where she builds accurate, scalable and transparent NLU systems. Before joining IBM Watson, Laura was a Researcher in the Scalable NLP group in IBM Research - Almaden, where she built and led the transfer of NLP technologies to multiple IBM products, including IBM BigInsights, IBM Streams and Watson Knowledge Studio, and completed customer engagements with Fortune 100 and multi-national organizations. Laura has been teaching NLP in universities, and developed two online courses in the process. Laura holds a Ph.D. in CS from University of California, Santa Cruz, and a B.S. in Computer Engineering from Politehnica University of Bucharest.
Marie Mateer: Associate Professor and Industry Liaison at Brandeis University in Computational Linguistics and an independent consultant in speech, dialog, and NLP. She started her career as a research scientist at BBN Technologies and over the next 20 years rose to VP of Commercial Speech before spinning out “EveryZing”, a digital media merchandising platform. Over the past decade, she has consulted for a broad range of companies on spoken dialog systems, language modeling, text analytics for call centers, analysis of medical records, speech recognition in simulation and training, and patent research.
Dan Roth: The Eduardo D. Glandt Distinguished Professor at the Department of Computer and Information Science, University of Pennsylvania. Roth is a Fellow of the AAAS, ACM, AAAI, and the ACL, and the winner of the 2017 John McCarthy Award. Roth is a co-founder and the chief scientist of NexLP, Inc. a startup that leverages the latest advances in NLP and Machine Learning in the legal and compliance domains. Prof. Roth got his B.A Summa cum laude in Mathematics from the Technion, Israel and his Ph.D in Computer Science from Harvard University in 1995.
Ethics in NLP Panel
This is an exciting time as we witness mature NLP technologies make their way into products and get deployed in the real world. However, as the technology become more broadly adopted, studies have shown that some solutions may contain biases that were not uncovered during testing in laboratory settings. The NAACL 2018 Industry Track includes a panel dedicated to addressing this topic. The panel consists of experts from both industry and academia, who focus their studies on ethical issues in NLP (and AI in general). They will discuss, among other topics, sources of biases that may creep into solutions, what we, as NLP practitioners, can do to raise awareness of such potential biases and reduce them, as well as societal impact of such unintended biases in deployed solutions.
Dirk Hovy (moderator) is an associate professor of computer science at the marketing department of Bocconi University in Milan, Italy. His research focuses on the interaction between socio-demographic factors, language, and NLP models, and the consequences for their use. He is also interested in ethical questions of model bias and algorithmic fairness. Dirk received his PhD in Computer Science from the University of Southern California, and holds an MA in sociolinguistics from the University of Marburg, Germany. He has authored multiple papers on a variety of NLP topics, and is one of the organizers of the first two workshops on ethics in NLP (EACL 2017 and NAACL 2018) and on the first workshop on abusive language (ACL 2017). Outside of research, Dirk enjoys cooking, reading, and leather-crafting, as well as picking up heavy things and putting them back down. You can find his CV, links to the papers, and more at www.dirkhovy.com
Margaret Mitchell is a Senior Research Scientist at Google, where she works on Ethical AI and is the technical lead for Google's ML Fairness initiative. Her research generally blends natural language processing, computer vision, cognitive science, and applied work in clinical and assistive domains.
Barbara Plank is an Associate Professor in Natural Language Processing at IT University of Copenhagen. She has previously held positions as assistant professor at the University of Groningen and the University of Copenhagen, and she did a postdoc at the University of Trento. Her research interests cover topics including learning under sample selection bias (domain adaptation, transfer learning), annotation bias and generally, semi-supervised and weakly-supervised learning (learning under limited supervision) for cross-domain and cross-lingual NLP.
Vinodkumar Prabhakaran is a currently postdoctoral fellow at the Stanford NLP lab, and received his PhD in Computer Science from Columbia University in 2015. In fall 2018, he will start as a research scientist at Google's Ethical AI team to work on issues around ethics and fairness in ML and NLP. His research falls in the interdisciplinary field of computational social sciences, with a focus on applying NLP for social good. He combines NLP techniques with social science methods in order to identify and address large scale societal issues, such as racial disparities in law enforcement, manifestations of power and gender at workplace, and online incivility such as condescension and gender bias.
Mark Yatskar is a post-doc at the Allen Institute for Artificial Intelligence and recipient of their Young Investigator Award. His primary research is in the intersection of language and vision, natural language generation, and ethical computing. He received his Ph.D. from the University of Washington with Luke Zettlemoyer and Ali Farhadi, in 2017 received the EMNLP best paper award and his work has been featured in Wired and the New York Times.