Artificial Intelligence

Taming the scientific literature: progress and challenges

Friday, November 09, 2018, 3:00pm - 4:00pm PDTiCal
6th Floor Conf Rm- #689
This event is open to the public.
NL Seminar
Waleed Ammar

Abstract: The magnitude and growth of the scientific literature can be overwhelming even for experienced researchers. Three years ago, the Allen Institute for Artificial Intelligence launched to understand and address the information needs of researchers. In this talk, I start by highlighting some of the lessons we learned from our 2M monthly actively users, and some of the key differences between academic and industrial research. Then, I describe three complementary directions for analyzing the scientific literature at scale. In the first direction, we extract meaningful structures such as entities, relationships and figures. In the second direction, we establish connections between different artifacts in the literature to facilitate navigation and enable complex querying capabilities. In the third direction, we try to address controversial questions in the literature by quantifying observable attributes at a large scale. I conclude with a short list of under-explored research opportunities with high potential in this domain.

Bio: Waleed Ammar is a senior research scientist at the Allen Institute for Artificial Intelligence where he leads the research efforts in the semantic scholar project. He is interested in developing NLP models with practical applications, especially in the scientific and medical domains and other data-constrained scenarios. Before pursuing his PhD at Carnegie Mellon University, Waleed an engineer at the machine translation group at MSR, a web developer at eSpace technologies, and a teaching assistant at Alexandria University. Waleed co-hosts the NLP highlights podcast with Matt Gardner.

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