Professional AssociationsProfessional Associations: Association for Computational Linguistics
Work Experience: [ CV ]
- NLP Chair, IBM, 2017 - present
- Research Scientist, IBM, 2014 - present
- Research Intern, Microsoft Research, Summer 2013
- Data & Tech Analyst Intern, Morgan Stanley, Summer 2011
Dr. Avi Sil is a Research Scientist in the Information Extraction and NLP group at IBM Research AI. He is also the Chair of the NLP professional community of IBM. His research focusses on making AI systems understand the meaning of natural language text. Most of his work has been on making sense of large unstructured web data applying machine learning algorithms: Extracting entities (names of persons, organizations, etc.), resolving them to big knowledge-bases (like Wikipedia) and extracting relationships between the entities. Currently, he is working on Question Answering algorithms by attaching world knowledge to systems.
Here's a recent article about his research on Entity Linking.
Avi completed his PhD in Computer Science under the supervision of his thesis advisor Alexander Yates. He also worked on Temporal Information Extraction in the Machine Learning Group at Microsoft Research, Redmond managed by Chris Burges and John Platt. His mentor was Silviu Cucerzan. He has more than 12 US patents filed all in the area of Artificial Intelligence and it's applications in various spheres.
- Slides from our ACL tutorial are now available here!
- (new) Will be co-ordinating the EDL track at TAC KBP 2018 along with Heng Ji. Please consider participating.
- (new) ACL paper on Neural Cross-lingual Coreference resolution has been accepted.
- Our ACL Tutorial website is now up!! Go check it out here.
- Giving the Multi-lingual Entity Discovery and Linking Tutorial at ACL 2018 along with Dan Roth, Heng Ji & Silviu Cucerzan.
- Area chair for COLING 2018
- Area chair for Information Extraction at NAACL 2018
- AAAI 2018 Paper accepted: Neural Cross-lingual Entity Linking
- Organizing ACL 2018 Workshop on "Relevance of Linguistic Structures in Neural NLP".