The 8th Workshop on Patent and Scientific Literature Translation


Invited talks

We will have the following invited speakers at PSLT 2019:

Yohei Matsutani

Yohei Matsutani (Japan Patent Office)

Utilization of Machine Translation in the Japan Patent Office toward improvement of accessibility for Patent Information.

Yohei Matsutani has served as Deputy Director at the Patent Information Policy Planning Office, Policy Planning and Coordination Department in the Japan Patent Office since July 2018. He engages in planning policies related to the translation of patent information. He joined the JPO as a patent examiner in 2004. In his 15 years’ career in the JPO, he has been involved in the patent examination of medical devices, analytical instruments.

Christof Monz

Christof Monz (University of Amsterdam)

Neural Machine Translation for Dynamic Domains

Christof Monz is an associate professor in computer science at the Informatics Institute, University of Amsterdam. His research interests lie in the area of multilingual natural language processing and machine translation in particular. Prior to joining the University of Amsterdam he worked as a lecturer at Queen Mary University of London and as a post-doctoral research fellow at the University of Maryland Institute for Advanced Computer Studies (UMIACS). He received a PhD in Computer Science from the University of Amsterdam in 2003.

Aurélie Névéol

Aurélie Névéol (LIMSI-CNRS)

Biomedical Natural Language processing in multiple languages: contribution of multilingual corpus and machine translation

Aurélie Névéol is a Senior Staff Scientist at the Centre National pour la Recherche Scientifique (CNRS). She received an MSc in Linguistics in 2002 and a PhD in Computer Science in 2005. She has more than 10 years experience in biomedical Natural Language Processing Research and has addressed the analysis of biomedical text from the litterature and from Electronic Health Reccords in French and in English. Recently, she has been focusing on clinical NLP for languages other than English. She has contributed to the development of representations of clinical information to support information extraction from EHR text, which can then be used for high throughput phenotyping. In the course of her work she has also contributed to the evaluation of research methods and workflows through her participation in the H2020 MIROR project and international evaluation campaigns such as CLEF eHealth and the biomedical task at WMT.