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Get to know the Amazon research community at NAACL 2019!

Amazon’s research teams are looking forward to meeting you at NAACL 2019. Come and visit us at the Amazon booth, and read on for more information about academic collaboration, career opportunities, and our teams.


NAACL 2019 Workshops
  • The Workshop on Shortcomings in Vision and Language - Spandana Gella 
  • The 2nd Workshop on Computational Models of Reference, Anaphora and Coreference - Yulia Grishina
  • The 6th Workshop on NLP for Similar Languages, Varieties and Dialects - Shervin Malmasi
NAACL 2019 Publications
  • OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference --- Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Xin Luna Dong, Andrew McCallum [pdf]
  • Continuous Learning for Large-scale Personalized Domain Classification - Han Li, Jihwan Lee, Sidharth Mudgal, Ruhi Sarikaya and Young-Bum Kim
  • Goal-Oriented End-to-End Chatbots with Profile Features in a Real-World Setting - Yichao Lu, Manisha Srivastava, Jared Kramer, Heba Elfardy, Andrea Kahn, Song Wang and Vikas Bhardwaj
  • Locale-agnostic Universal Domain Classification Model in Spoken Language Understanding - Jihwan Lee, Ruhi Sarikaya and Young-Bum Kim
  • In Other News: A Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited Data - Nishant Prateek, Mateusz Łajszczak, Roberto Barra-Chicote, Thomas Drugman, Jaime Lorenzo-Trueba, Thomas Merritt, Srikanth Ronanki, Trevor Wood [arxiv]
  • Learning When Not to Answer: A Ternary Reward Structure for Reinforcement Learning based Question Answering - Frederic Godin, Anjishnu Kumar, Arpit Mittal [pdf]
  • Scaling Multi-Domain Dialogue State Tracking via Query Reformulation - Pushpendre Rastogi, Arpit Gupta, Tongfei Chen and Mathias Lambert []
  • Neural Text Normalization with Subword Units - Courtney Mansfield, Ming Sun, Yuzong Liu, Ankur Gandhe, Björn Hoffmeister
  • ComQA: A Community-sourced Dataset for Complex Factoid Question Answering with Paraphrase Clusters - Abdalghani Abujabal, Rishiraj Saha Roy, Mohamed Yahya and Gerhard Weikum
  • Joint Multiple Intent Detection and Slot Labeling for Goal-Oriented Dialog - Rashmi Gangadharaiah, Balakrishnan Narayanaswamy
  • Guiding Extractive Summarization with Question-Answering Rewards - Kristjan Arumae, Fei Liu
  • Relation Extraction using Explicit Context Conditioning - Gaurav Singh, Parminder Bhatia
  • Active Learning for New Domains in Natural Language Understanding - Imre Kiss, John Kearney, Spyros Matsoukas, Stanislav Peshterliev
  • Aligning Vector-spaces with Noisy Supervised Lexicon - Noa Yehezkel Lubin
  • Cross-lingual Transfer Learning for Japanese Named Entity Recognition - Judith Gaspers, Penny Karanasou, Spandana Gella
  • Enhancing Key-Value Memory Neural Networks for Knowledge Based Question Answering - Zhiguo Wang
  • Fast Concept Mention Grouping for Concept Map-based Multi-Document Summarization - Tobias Falke
  • Generating Token-Level Explanations for Natural Language Inference - Christos Christodoulopoulos
  • Practical Semantic Parsing for Spoken Language Understanding - Rahul Goel
  • Pun Generation with Surprise - He He
  • Simple Question Answering with Subgraph Ranking and Joint-Scoring - Angeliki Metallinou, Anuj Goyal, Tagyoung Chung
  • Strong Baselines for Complex Word Identification Across Multiple Languages - Elisabeth Fritzsch
  • VQD: Visual Query Detection in Natural Sciences - Karan Jariwala
  • When Open Information Extraction Meets the Semi-Structured Web - Prashant Shiralkar
Internships for PhD Students

We offer 3-6 month internships year-round, with opportunities in Aachen, Atlanta, Austin, Bangalore, Barcelona, Berlin, Boston, Cambridge, Cupertino, Graz, Haifa, Herzliya, Manhattan Beach, New York, Palo Alto, Pasadena, Pittsburgh, San Francisco, Shanghai, Seattle, Sunnyvale, Tel Aviv, Tübingen, Turin, and Vancouver. To apply, email your resume to, and let us know if there are any specific locations, teams, or research leaders that you are interested in working with. 

Amazon and NSF Collaborate to Accelerate Fairness in AI Research

NSF and Amazon are partnering to jointly support computational research focused on fairness in AI, with the goal of contributing to trustworthy AI systems that are readily accepted and deployed to tackle grand challenges facing society. NSF has long supported transformative research in artificial intelligence (AI) and machine learning (ML). The resulting innovations offer new levels of economic opportunity and growth, safety and security, and health and wellness. 

Check out the details here

re:MARS 2019

Artificial intelligence is changing every industry. Join us at Amazon re:MARS, a new global AI event on Machine Learning, Automation, Robotics, and Space, to learn why and how to apply the latest AI advances in your business and work. re:MARS is inspired by MARS, an event hosted by Jeff Bezos that brings together leading minds to advance a golden age of innovation. re:MARS is your opportunity to participate, combining the latest in forward-looking science with practical applications. 

Job Opportunities for Graduating Students and Experienced Researchers

We are looking for results-driven individuals who can apply advanced machine learning techniques, love to work with data, are deeply technical, and highly innovative. If you long for the opportunity to invent and build solutions to challenging problems that directly impact the way Amazon transforms the consumer experience, we are the place for you. To apply, email your resume to, and let us know if there are any specific locations, teams, or research leaders that you are interested in working with. 

Amazon Web Services (AWS) Research Grants

In partnership with Machine Learning@Amazon, AWS offers up to $20,000 in compute tokens each quarter to professors and students. Academics have used these grants for projects ranging from Hack End weekends to massive MRI imaging projects. AWS provides building blocks for developing applications ranging from Elastic MapReduce for Hadoop analytics to fast and scalable storage with Amazon DynamoDB. Learn more & apply here.

Amazon Research Awards

ARA is an unrestricted gift to recognize exceptional faculty, and fund projects leading toward a PhD degree or conducted as a part of post-doctoral work. Each selected proposal is assigned an Amazon research contact, as we believe that both sides benefit from direct interaction on the topic of their research. We invite ARA recipients to visit Amazon offices worldwide to give talks related to their work and meet with our research groups face-to-face. We encourage ARA recipients to publish the outcome of the project and commit any related code to open source code repositories. Learn more here.

Alexa Prize

The Alexa Prize is an annual competition for university students dedicated to accelerating the field of conversational AI. Learn more at

Amazon Scholars

Amazon Scholars is a program for academic leaders to work with Amazon in a flexible capacity, ranging from part-time to full-time research roles. Learn more at:

Diversity at Amazon

We are a company of builders working on behalf of a global customer base. Diversity is core to our leadership principles, as we seek diverse perspectives so that we can be “Right, A Lot”. We welcome people from all backgrounds and perspectives to innovate with us. Learn more at

Publishing at Amazon

Amazon is committed to innovating at the frontiers of machine learning and artificial intelligence. Our scientists are encouraged to engage in the research community in the form of written publications, open source code and public datasets. We have instituted a new, fast-track publication approval process, to help share our research efforts as quickly as possible, while maintaining the highest standards of quality. Check out some of our most recent publications here


Meet a few Amazonians working in NLP

Natural Language Processing at Amazon

"I spoke to the future and it listened" - Gizmodo

Meet the team of world-class scientists behind Alexa.

Graduate Research Careers

Learn more about graduate research careers for PhD and Masters students.

Amazon Lex - Quickly Build Conversational Interfaces

With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer.

Learn more about Amazon Polly

Amazon Polly is a service that turns text into lifelike speech, making it easy to add voice to your website, mobile app, or device.

Introducing the Alexa Prize

The Alexa Prize is an annual competition for university students dedicated to accelerating the field of conversational AI.

2017 Alexa Prize Finals

Learn more about the Alexa Prize: