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Cécile Paris

  • Associate Investigator


Current Role:

Dr Cécile Paris is a Chief Research Scientist at Data61, and the Director for the Collaborative Intelligence (CINTEL) FSP, a CSIRO-wide research programme about leveraging the intelligences and capabilities of humans and machines to form the best performing teams. Previously, she was the Group Leader of Knowledge Discovery and Management, now called Humans and Machines, within the Analytics and Decision Sciences Research Programme at CSIRO’s Data61.

Short Biography:

Cecile received her PhD in Artificial Intelligence (AI) (more specifically in Natural Language Processing and User Modelling) in 1987 from Columbia University (New York) and my Bachelor degree from the University of California in Berkeley. Her research has focused on Natural Language Processing (also called Computational Linguistics, and Language Technologies) and User Modelling throughout her career. She joined the Information Sciences Institute (ISI), an AI research laboratory in Marina del Rey (Los Angeles, Ca), where she stayed until 1996, working on knowledge based systems and Explainable AI. She then moved to the UK (ITRI, at the University of Brighton, UK), where she researched multilingual generation systems. Cecile joined CSIRO late 1996, creating the Natural Language Processing team (now called “Language and Social Computing”, currently led by Dr Stephen Wan). She was elected a Fellow of the Australian Academy of Technology & Engineering (ATSE) in 2016 and a Fellow of the Royal Society of NSW in 2019.

With respect to natural language, she is interested in (1) unlocking information contained in textual form so as to make it available for reasoning and decision making – this might be obtaining social insights through NLP and Social Media Analytics, or obtaining information from (textual) enterprise documents or scientific publications; (2) assisting people with their information needs in the digital age, where information is growing at an unprecedented pace and where new types of data are becoming available, (3) understanding how people communicate with each other and with information, and (4) doing large scale text analytics (e.g., on social media) so as to provide domain analysts new data to gain insights in their domain.

Research Interests: Natural Language Processing; Social Media Analytics; Social Computing; Computer Human Interaction and Intelligent User Interfaces; User Modelling; Collaborative Intelligence; Collaboration and Computer Supported Collaborative Work (CSCW); Information Retrieval; Digital Libraries; Data Integration and Data Fusion; Social-Technical Systems.

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