Being part of a research institute in start-up mode, helping to build a strong team doing world class research, and at the same time experiencing a different environment in terms of culture and language, geography and climate.
As principal scientist in the Arabic language technologies group Stephan is responsible to help define the overall research agenda of QCRI and of the ALT team in particular.
His own research focus is on machine translation, especially the so-called statistical machine translation (SMT), where statistical modeling and machine learning techniques are used to learn from existing (human) translations how to translate new sentences. In the team’s research they deal with fundamental questions like optimization in SMT, integrating morphology, novel reordering models, etc, but also how this can be turned into useful applications to support real-live multilingual communication and information access.
An additional interest, which Stephan hopes to explore more in the future, is to apply language technologies in educational applications. In particular, QCRI’s ALT team has started to develop CALL (computer assisted language learning) applications for Arabic.
Before joining QCRI Stephan was research scientist at CMU, Pittsburgh, where he advised 10 PhD and 8 Master students, also visiting students from other universities, and led or participated in a number of research projects, funded by NSF and DARPA, including TIDES and GALE.
In the News
VLDB is a premier annual international forum for data management and database researchers, vendors, practitioners, application developers, and users.
QCRI is the local host for EMNLP 2014. EMNLP is organized by SIGDAT, the Association for Computational Linguistics special interest group for linguistic data and corpus-based approaches to natural language processing.
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