29 Amazon Research Awards recipients announced

Awardees, who represent 25 universities in seven countries, have access to Amazon public datasets, along with AWS AI/ML services and tools.

Amazon Research Awards (ARA) provides unrestricted funds and AWS Promotional Credits to academic researchers investigating various research topics in multiple disciplines. This cycle, ARA received many excellent research proposals from across the world and today is publicly announcing 29 award recipients who represent 25 universities in seven countries.

This announcement includes awards funded under five call for proposals during the spring 2022 cycle: AI for Information Security, Alexa – Fairness in AI, Amazon Advertising, Amazon Science Community and Machine Learning University, and AWS AI: Human-in-the-loop machine learning and annotation.

Proposals were reviewed for the quality of their scientific content and their potential to impact both the research community and society.

Recipients have access to more than 300 Amazon public datasets and can utilize AWS AI/ML services and tools through their AWS Promotional Credits. Recipients also are assigned an Amazon research contact who offers consultation and advice, along with opportunities to participate in Amazon events and training sessions.

Additionally, Amazon encourages the publication of research results, presentations of research at Amazon offices worldwide, and the release of related code under open-source licenses.

“Scientists and engineers are at their best when they’re inventing on behalf of customers," said Brent Werness, manager of applied science with Machine Learning University. "But how does that invention happen? And what can we do to help scientists and engineers do their best work? Answering these questions requires a sustained, interdisciplinary research agenda, and our 2022 Amazon Research Award recipients will take one more step toward understanding.”

Top row, left to right: Vardan Avagyan, Yakov Bart, Stevie Chancellor, Muhao Chen, Bas Donkers, Chuang Gan, Diego Gomez-Zara; second row, left to right: Omer Levy, Zhou Li, Vidya Muthukumar, Gijs Overgoor, Ashwin Pananjady, Xiao Qiao, Christian Schlereth; third row, left to right: Shuba Srinivasan, Damien Teney, Misha Teplitskiy, Berk Ustun, Dashun Wang, Xiaolong Wang, Yang Weng; and bottom row, left to right: Eric Xing, Diyi Yang, Gokhan Yildirim, Heng Yin, and Hanzhe Zhang are among the recipients from the Amazon Research Awards Spring 2022 call for proposals.
Top row, left to right: Vardan Avagyan, Yakov Bart, Stevie Chancellor, Muhao Chen, Bas Donkers, Chuang Gan, Diego Gomez-Zara; second row, left to right: Omer Levy, Zhou Li, Vidya Muthukumar, Gijs Overgoor, Ashwin Pananjady, Xiao Qiao, Christian Schlereth; third row, left to right: Shuba Srinivasan, Damien Teney, Misha Teplitskiy, Berk Ustun, Dashun Wang, Xiaolong Wang, Yang Weng; and bottom row, left to right: Eric Xing, Diyi Yang, Gokhan Yildirim, Heng Yin, and Hanzhe Zhang are among the recipients from the Amazon Research Awards Spring 2022 call for proposals.

ARA funds proposals two times a year in a variety of research areas. Applicants are encouraged to visit the ARA call for proposals page for more information or send an email to be notified of future open calls.

The table below lists, in alphabetical order, spring 2022 cycle call-for-proposal recipients.

RecipientUniversityResearch title
Vardan AvagyanErasmus University RotterdamRole of consumer mindset metrics in optimal ad decisions
Yakov BartNortheastern UniversityUsing video summarization for generating effective short video ads
Amrit Singh BediUniversity of Maryland, College ParkEnsuring fairness via federated learning beyond consensus
Stevie ChancellorUniversity of Minnesota, Twin CitiesCollaborative and socially translucent task instructions for emotionally heavy and subjective annotation tasks
Muhao ChenUniversity of Southern CaliforniaOn faithfulness of information extraction
Bas DonkersErasmus University NetherlandsReal-time personalization in dynamic environments
Chuang GanUMass AmherstAuto-labeling through neuro-symbolic learning for visual and text data
Diego Gomez-ZaraUniversity Of Notre DameCreating and designing disruptive teams: Experiments and models for assessing teams’ disruption
Pallassana (P. K.) KannanUniversity of Maryland College ParkMeasuring the synergy across marketing touchpoints using transformers
Omer LevyTel Aviv UniversityExplaining and mitigating adverse biases in large language models via natural language instructions
Zhou LiUniversity Of California, IrvineAccurate, scalable and robust attack provenance on discrete temporal graph
Dinesh ManochaUniversity of Maryland, College ParkEnsuring fairness via federated learning beyond consensus
Vidya MuthukumarGeorgia Institute of TechnologyFramework for learning from online bidding
Gijs OvergoorRochester Institute Of TechnologyUsing video summarization for generating effective short video ads
Ashwin PananjadyGeorgia Institute of TechnologyFramework for learning from online bidding
Xiao QiaoCity University of Hong KongPredicting successful scientific collaborations
Christian SchlerethWHU Germany Otto Beisheim School of ManagementThe power of the climate friendly badge
Shuba SrinivasanBoston UniversityRole of consumer mindset metrics in optimal ad decisions
Damien TeneyIdiap Research InstituteAddressing underspecification for improved fairness and robustness in conversational AI
Misha TeplitskiyUniversity of MichiganLearning by reviewing
Berk UstunUniversity of California, San DiegoParticipatory personalization in machine learning
Dashun WangNorthwestern UniversityCreating and designing disruptive teams: Experiments and models for assessing teams’ disruption
Xiaolong WangUniversity of California, San DiegoOpen world object discovery and tracking with grouping vision transformers
Yang WengArizona State UniversityReinforcement learning twins: granular level recommendations with causal interpretations on amazon assortment via limited tests
Eric XingCarnegie Mellon UniversityA faster and more accurate secure model serving framework on the cloud
Diyi YangStanford UniversityHuman-in-the-loop for long text generation
Gokhan YildirimImperial College LondonRole of consumer mindset metrics in optimal ad decisions
Heng YinUniversity of California, RiversideNext-generation AI-powered binary diffing
Hanzhe ZhangMichigan State UniversityPredicting successful scientific collaborations

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