Get to know the Amazon research community at The Web Conf 2018!
Amazon’s research teams are looking forward to meeting you at The Web Conf. Come and visit us at the Amazon booth, and read on for more information about academic collaboration, career opportunities, and our teams.
Keynote Speaker: Ruhi Sarikaya (Amazon) | Conversational AI for Interacting with Digital and Physical World
Invited Speaker (The Big Web Track): Luna Dong (Amazon) | Challenges and Innovations in Building a Product Knowledge Graph
International World Wide Web Conference Committee (IW3C2): Yoelle Maarek
Test of Time Award Selection Committee & Chair: Yoelle Maarek
Senior Program Committee Member: Liane Lewin-Eytan (Amazon)
Research Tracks Program Committee Members: Abraham Bagherjeiran (Amazon A9), Stijn Heymans (Amazon), Amir Ingber (Amazon), Erik Selberg (Amazon), Kevin Small (Amazon), Liane Lewin-Eytan (Amazon), Alex Libov (Amazon), Aston Zhang (Amazon)
Accepted Papers & Posters
“A Sparse Topic Model for Extracting Aspect-Specific Summaries from Online Reviews” | Authors: Vineeth Rakesh (Arizona State University), Weicong Ding (Amazon), Aman Ahuja (Virginia Tech), Nikhil Rao (Amazon), Yifan Sun (Technicolor), Chandan K. Reddy (Virginia Tech)
“Leveraging Crowdsourcing Data for Deep Active Learning - An Application: Learning Intents in Alexa” | Authors: Jie Yang (Delft University of Technology, Amazon), Thomas Drake (Amazon A9), Andreas Damianou (Amazon), Yoelle Maarek (Amazon)
“Bayesian Models for Product Size Recommendations” | Authors: Vivek Sembium (Amazon), Rajeev Rastogi (Amazon), Lavanya Sita Tekumalla (Amazon), Atul Saroop (Amazon)
"Handling Confounding for Realistic Offline-Policy Evaluation" | Authors: Saurabh Sohoney (Amazon), Nikita Prabhu (Amazon), Vineet Chaoji (Amazon)
"Retrieving Information from Multiple Sources" | Authors: Anurag Roy (Polaris Networks), Kripabandhu Ghosh (IIT Kanpur), Moumita Basu (IIEST Shibpur), Parth Gupta (Amazon), and Saptarshi Ghosh (IIT Kharagpur)
“A3embed: Attribute Association Aware Network Embedding” | Workshop on Mining Attributed Networks | Authors: Jihwan Lee (Amazon), Sunil Prabhakar (Purdue)
“Learning Large Scale Ordinal Ranking Model via Divide-and-Conquer Technique” | Extreme Multilabel Classification for Social Media Workshop | Authors: Lu Tang (University of Michigan, Amazon), Sougata Chaudhuri (Amazon A9), Abraham Bagherjeiran (Amazon A9), Ling Zhou (Carnegie Mellon University)
"Automated Extractions for Machine Generated Mail" | The Big Web Track | Authors: D. Di Castro (Yahoo), Iftah Gamzu (Amazon), Irena Grabovitch-Zuyev (Yahoo), Liane Lewin-Eytan (Amazon), Abhinav Pundir (Yahoo), Nil Ratan Sahoo (Yahoo), Michael Viderman (Yahoo)
CredEye: A Credibility Lens for Analyzing and Explaining Misinformation | Subhabrata Mukherjee (Amazon)
Internships for PhD Students
We offer 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, Seattle, Sunnyvale, Tel Aviv, Tübingen, Turin, and Vancouver. To apply, email your resume to firstname.lastname@example.org, and let us know if there are any specific locations, teams, or research leaders that you are interested in working with.
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. Apply to one of the job postings below or send your resume directly to email@example.com.
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.
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.
The Alexa Prize is an annual competition for university students dedicated to accelerating the field of conversational AI. Learn more at alexaprize.com.
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 amazon.com/diversity.
Amazon Scholars is a new program for academic leaders to work with Amazon in a flexible capacity, ranging from part-time to full-time research roles. Learn more at amazon.jobs/scholars
Learn more about Amazon's research teams:
Customer-obsessed Science at Amazon
Scientists at Amazon explain the customer-obsessed science they're tackling to bring Amazon products and services to life.
“I spoke to the future and it listened.” - Gizmodo. Meet the team of world-class scientists behind Alexa.
The history of Amazon's recommendation algorithm
Consumer division CEO, Jeff Wilke, discusses the history of Amazon's recommendation algorithm at re:MARS 2019.
Ever wonder how Amazon delivers your packages so quickly? In some cases, robots.
The Shopping Core Team
Shopping Core owns many of the technical features and functionality for Amazon.com
The Social Shopping Team
Social Shopping is responsible for our product reviews, recommendations, Wishlist and much more.