105 Amazon Research Awards recipients announced

Awardees, who represent 51 universities in 15 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 105 award recipients who represent 51 universities in 15 countries.

This announcement includes awards funded under six call for proposals during the fall 2023 cycle: AI for Information Security, Automated Reasoning, AWS AI, AWS Cryptography and Privacy, AWS Database Services, and Sustainability. Proposals were reviewed for the quality of their scientific content and their potential to impact both the research community and society.

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.

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.

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“We received a fantastic response to the cryptography and privacy engineering’s call for proposals. This was the first time we offered ARAs for cryptography and privacy, and the response far exceeded our expectations, in terms of both the number and quality of the proposals,” said Rod Chapman, senior principal applied scientist with AWS Cryptography. “Advanced cryptography plays a crucial role in building trust with our customers and regulators, especially in emerging domains such as cryptographic computing, generative AI, and privacy-preserving applications. We look forward to working with the new principal investigators to bring ever more impactful cryptographic technologies to fruition.”

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“Given that data is central to Amazon’s core businesses, I am excited by this opportunity to collaborate with universities on cutting-edge technologies for modern database systems,” said Doug Terry, vice president and distinguished scientist in AWS Database and AI Leadership. “These Amazon Research Awards allow us to support projects that have the potential for substantial advancement in important areas from correctness testing of SQL queries to new data models for generative AI applications.”

ARA funds proposals throughout the 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 tables below list, in alphabetical order by last name, fall 2023 cycle call-for-proposal recipients, sorted by research area.

AI for Information Security

Photo grid shows the recipients of the 2023 fall AI for information security Amazon Research Awards

RecipientUniversityResearch title
Murat KocaogluPurdue UniversityCausal Anomaly Detection from Non-stationary Time-series in the Cloud
Hui LiuMichigan State UniversityHarnessing the Power of Weakly-Supervised Graph Representation Learning for Cybersecurity
Xiaorui LiuNorth Carolina State UniversityHarnessing the Power of Weakly-Supervised Graph Representation Learning for Cybersecurity
Thomas PasquierUniversity of British ColumbiaBuilding Robust Provenance-based Intrusion Detection
Michalis PolychronakisStony Brook UniversitySafeTrans: AI-assisted Transcompilation to Memory-safe Languages

Automated Reasoning

Photo grid shows the recipients of the 2023 fall automated reasoning Amazon Research Awards

RecipientUniversityResearch title
Armin BiereUniversity of FreiburgFrom Mavericks to Teamplayers: Fostering Solver Cooperation in Distributed SAT Solving
Victor BrabermanUniversidad de Buenos AiresAbstractions for Validating Distributed Protocol Reference Implementations
Varun ChandrasekaranUniversity of Illinois Urbana-ChampaignAutomating Privacy Compliance
Maria ChristakisTU WienTesting Dafny for Unsoundness and Brittleness Bugs
Werner DietlUniversity of WaterlooOptional Type Systems for Model-Implementation Consistency
Alastair DonaldsonImperial College LondonValidating Compilers for the Dafny Verified Programming Language
Azadeh FarzanUniversity of TorontoBetter Predictability in Dynamic Data Race Detection
Sicun GaoUniversity Of California, San DiegoProof Optimization and Generalization in dReal
Tobias GrosserUniversity Of CambridgeCorrect and High-Performance Domain-Specific Compilation with Lean and MLIR
Andrew HeadUniversity Of PennsylvaniaTYCHE: An IDE for Property-Based Testing
Kihong HeoKorea Advanced Institute Of Science and Technology - KAISTGenerative Translation Validation for JIT Compiler in the V8 JavaScript Engine
Frans KaashoekMassachusetts Institute of TechnologyFlotilla: Compositional Formal Verification of Liveness of Distributed Systems Implementations
Baris KasikciUniversity of Washington - SeattlePrivacy-Conscious Failure Reproduction for Root Cause Diagnosis in Large-Scale Distributed Systems
Laura KovacsTU WienQuAT: Quantifiers with Arithmetic Theories are Friends with Benefits
Shriram KrishnamurthiBrown UniversityParalegal: Scalable Tooling to Find Privacy Bugs in Application Code
Corina PasareanuCarnegie Mellon UniversityProving the Absence of Timing Side Channels in Cryptographic Applications
Jean Pichon-PharabodAarhus UniversityValidating Isolation of Virtual Machines in the Cloud
Benjamin PierceUniversity Of PennsylvaniaTYCHE: An IDE for Property-Based Testing
Ruzica PiskacYale UniversityDemocratizing the Law - Using LLMs and Automated Reasoning for Legal Reasoning
Malte SchwarzkopfBrown UniversityParalegal: Scalable Tooling to Find Privacy Bugs in Application Code
Peter SewellUniversity Of CambridgeThe Foundations of Cloud Virtual-machine Isolation
Scott ShapiroYale UniversityDemocratizing the Law - Using LLMs and Automated Reasoning for Legal Reasoning
Geoffrey SutcliffeUniversity Of MiamiAutomated Theorem Proving Community Infrastructure in the AWS Cloud
Joseph TassarottiNew York UniversityAsynchronous Couplings for Probabilistic Relational Reasoning in Dafny
Sebastian UchitelUniversidad de Buenos AiresAbstractions for Validating Distributed Protocol Reference Implementations
Josef UrbanCzech Technical UniversityLearning Based Synthesis Meets Learning Guided Reasoning
Thomas WiesNew York UniversityAutomating Privacy Compliance
Nickolai ZeldovichMassachusetts Institute of TechnologyFlotilla: Compositional Formal Verification of Liveness of Distributed Systems Implementations

AWS AI

Photo grid shows the recipients of the 2023 fall AWS AI Amazon Research Awards

RecipientUniversityResearch title
Pulkit AgrawalMassachusetts Institute Of TechnologyAdapting Foundation Models without Finetuning
Niranjan BalasubramanianStony Brook UniversityAn API Sandbox for Complex Tasks on Common Applications
Osbert BastaniUniversity Of PennsylvaniaUncertainty Quantification for Trustworthy Language Generation
Matei CiocarlieColumbia UniversityDo You Speak EMG? Generative Pre-training on Electromyographic Signals for Controlling a Rehabilitation Robot after Stroke
Caiwen DingUniversity of ConnecticutGraph of Thought: Boosting Logical Reasoning in Large Language Models
Yufei DingUniversity Of California, San DiegoA Hollistic Compiler and Runtime System for Efficient and Scalable LLM Serving
Xinya DuUniversity Of Texas At DallasProcess-guided Fine-tuning for Answering Complex Questions
Luciana FerrerUniversity of Buenos Aires - CONICETEfficient Adaptation of Generative Language Models through Unsupervised Calibration
Jakob FoersterUniversity Of OxfordCompute-only Scaling of Large Language Models
Nikhil GargCornell UniversityRecommendation systems in high-stakes settings
Georgia GkioxariCalifornia Institute Of TechnologyTowards a 3D Foundation Model: Recognize and Reconstruct Anything
Tom GoldsteinUniversity of MarylandBuilding Safer Diffusion Models
Aditya GroverUniversity of California, Los AngelesPersonalizing Multimodal Generative Models via In-Context Preference Modeling
Albert GuCarnegie Mellon UniversityScaling the Next Generation of Foundation Model Architectures
Mahdi S. HosseiniConcordia UniversityToward Auto-Populating Synoptic Reports in Diagnostic Pathology
Maliheh IzadiDelft University Of TechnologyUnderstanding and Regulating Memorization in Large Language Models for Code
Vijay Janapa ReddiHarvard UniversityBenchmarking the Safety of Generative AI Models with Data-centric AI Challenges
Adel JavanmardUniversity of Southern CaliforniaReliable AI for Generation of Medical Reports from MRI Scans
Jianbo JiaoUniversity Of BirminghamPCo3D: Physically Plausible Controllable 3D Generative Models
Subbarao KambhampatiArizona State UniversityUnderstanding and Leveraging Planning, Reasoning & Self-Critiquing Capabilities of Large Language Models
Kangwook LeeUniversity Of Wisconsin–MadisonInformation and Coding Theory-Based Framework for Prompt Engineering
Ales LeonardisUniversity Of BirminghamPCo3D: Physically Plausible Controllable 3D Generative Models
Anqi LiuJohns Hopkins University(Multi-)Calibrated Active Learning under Subpopulation Shift
Lydia LiuPrinceton UniversityFrom Predictions to Positive Impact: Foundations of Responsible AI in Social Systems
Song MeiUniversity Of California, BerkeleyMathematical Foundations and Physical Principles of Foundation Models and Generative AI
Pablo PiantanidaNational Centre for Scientific Research (CNRS)Efficient Adaptation of Generative Language Models through Unsupervised Calibration
Chara PodimataMassachusetts Institute Of TechnologyResponsible AI through User Incentive-Awareness
Bhiksha RajCarnegie Mellon UniversityText and Speech Large Language Models
Christian RupprechtUniversity Of OxfordViewset Diffusion for Probabilistic 3D Reconstruction
Olga RussakovskyPrinceton UniversityDiffusion models: Generative models beyond data generation
Vatsal SharanUniversity Of Southern CaliforniaDebiasing ML-based Decision Making using Multicalibration
Abhinav ShrivastavaUniversity Of MarylandAudio-conditioned Diffusion Models for Generating Lip-synchronized Videos
Rachee SinghCornell UniversityAccelerating collective communication for distributed ML
Vincent SitzmannMassachusetts Institute Of Technology2D and 3D Animation via Image-Conditional Generative Flow Models
Justin SolomonMassachusetts Institute Of TechnologyLightweight Algorithms for Generative AI
Mahdi SoltanolkotabiUniversity of Southern CaliforniaReliable AI for Generation of Medical Reports from MRI Scans
Qian TaoDelft University of TechnologyΦ-Generative Medical Imaging by Physics and AI (PhAI)
Yapeng TianUniversity Of Texas At DallasIntegrating Visual Alignment and Text Interaction for Multi-modal Audio Content Generation
Sherry Tongshuang WuCarnegie Mellon UniversityGenerating Deployable Models from Natural Language Instructions through Adaptive Data Curation
Florian TramerEth ZurichCan Technology Protect us from Generative AI?
Arie van DeursenDelft University Of TechnologyUnderstanding and Regulating Memorization in Large Language Models for Code
Andrea VedaldiUniversity Of OxfordViewset Diffusion for Probabilistic 3D Reconstruction
Carl VondrickColumbia UniversityViper: Visual Inference via Python Execution for Reasoning
Xiaolong WangUniversity of California, San DiegoGenerating Compositional 3D Scenes and Embodied Tasks with Large Language Models
Eric WongUniversity Of PennsylvaniaAdversarial Manipulation of Prompting Interfaces
Saining XieNew York UniversityImage Sculpting: Precise Image Generation and Editing with Interactive Geometry Control
Rex YingYale UniversityDiff-H: Hyperbolic Text-to-Image Diffusion Generative Model
Minlan YuHarvard UniversityTroubleshooting Distributed Training Systems
Zhiru ZhangCornell UniversityA Unified Approach to Tensor Graph Optimization

AWS Cryptography and Privacy

Photo grid shows the recipients of the 2023 fall AWS Cryptography and Privacy Amazon Research Awards

RecipientUniversityResearch title
Christopher BrzuskaAalto UniversitySecure Messaging: Updates Efficiency & Verification
Tevfik BultanUniversity of California, Santa BarbaraDetecting and Quantifying Information Leakages in Crypto Libraries
Muhammed EsginMonash UniversityPractical Post-Quantum Oblivious Pseudorandom Functions Supporting Verifiability
Nadia HeningerUniversity of California, San DiegoBringing Modern Security Guarantees to End-to-End Encrypted Cloud Storage
Tal MalkinColumbia UniversityCryptographic Techniques for Machine Learning
Peihan MiaoBrown UniversityAdvancing Private Set Intersection for Wider Industrial Adoption
Virginia SmithCarnegie Mellon UniversityRethinking Watermark Embedding and Detection for LLMs
Ron SteinfeldMonash UniversityPractical Post-Quantum Oblivious Pseudorandom Functions Supporting Verifiability

AWS Database Services

Photo grid shows the recipients of the fall 2023 AWS Database Services Amazon Research Awards

RecipientUniversityResearch title
Lei CaoUniversity Of ArizonaSEED: Simple, Efficient, and Effective Data Management via Large Language Models
Natacha Crooks

University Of California, Berkeley

Mammoths Are Slow: The Overlooked Transactions of Graph Data
Samuel MaddenMassachusetts Institute Of TechnologySEED: Simple, Efficient, and Effective Data Management via Large Language Models
Manuel RiggerNational University Of SingaporeDemocratizing Database Fuzzing

Kexin Rong

Georgia Institute Of Technology

Dynamic Data Layout Optimization with Worst-case Guarantees

Sustainability

Photo grid shows the recipients of the fall 2023 sustainability Amazon Research Awards

RecipientUniversityResearch title
Kate ArmstrongNew York Botanical GardenVERDEX: remote sensing of plant biodiversity
Praveen BolliniUniversity Of HoustonData-driven design and optimization of selective nanoporous catalysts for biofuel conversion
Brandon BukowskiJohns Hopkins UniversityData-driven design and optimization of selective nanoporous catalysts for biofuel conversion
Alan EdelmanMassachusetts Institute of TechnologyScientific Machine Learning with Application to Probabilistic Climate Forecasting and Sustainability
Kosa Goucher-LambertUniversity of California, BerkeleyLCAssist: An Interactive System for Life-Cycle-Informed Sustainable Design Decision-Making
Vikram IyerUniversity of Washington - SeattleData-Driven Sustainable Polymer Design for Circuits, Packaging, and Actuators
Can LiPurdue UniversityDesign and Analysis of Sustainable Supply Chains Using Optimization and Large Language Models
Damon LittleNew York Botanical GardenVERDEX: remote sensing of plant biodiversity
Aniruddh VashisthUniversity of Washington - SeattleData-Driven Sustainable Polymer Design for Circuits, Packaging, and Actuators
Ming XuTsinghua UniversityAdvancing Sustainable Practices in the AI Era: Integrating Large Language Models for Automated Life Cycle Assessment Modeling

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