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 70 award recipients who represent 49 universities in 11 countries.
This announcement includes awards funded under 6 calls for proposals during the fall 2025 cycle: AI for Information Security, Agentic AI , Automated Reasoning, AWS Cryptography, Cybersecurity and Anti-Abuse Technologies, 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 700 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.
"Fraud and abuse evolve at the speed of the technologies that bad actors exploit. Since we can only defend against what we can measure, the science of studying those technologies has to keep pace," said Dhruv Kuchhal, Applied Scientist, Special Projects & Invest-Fixed. "Through ARA, we bring together experts across industry and academia to tackle these problems upstream and publish defenses that systematically raise bad actors' operating costs and erode their ROI as they spread across the ecosystem. This not only strengthens Amazon, but the broader Web, including online shopping customers, sellers and brands who build businesses online, and the platforms and payment rails that tie them together. We were impressed by the quality and volume of proposals we received — a strong signal that the field is raising the bar for Web users everywhere — and we look forward to working with the new recipients to turn this research into lasting, ecosystem-wide improvements in fraud and abuse prevention."
“AI is reshaping cybersecurity faster than ever in advancing how we detect threats and defend systems, ”said Wei Ding, Applied Science Manager, GuardDuty, AWS. “At the same time, agentic AI requires stronger guarantees of safety, robustness, and trust worthiness. Since 2020, our team has funded security research that solves some of the biggest challenges for the industry. We’re pleased to continue our tradition of fostering innovation through these latest research projects addressing agentic AI security, AI-powered incident response, and threat detection in agentic AI systems and cloud environments, among other exciting areas.”
ARA funds proposals throughout the year in a variety of research areas. Applicants are encouraged to visit our 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 2025 cycle call-for-proposal recipients, sorted by research
AI for Information Security
Recipient |
University |
Research title |
Virginia Polytechnic Institute and State University |
CortexCTI: A Unified Threat Intelligence Engine for Knowledge-Driven Cloud Threat Detection and Response |
|
Texas A&M University |
New Benchmark and Defense on Prompt Injection in Agentic AI Systems |
|
Arizona State University |
Securing Agentic AI: From Local Detection to Global Assurance |
|
The University of Edinburgh |
Exploit-driven AI Agents for vulnerability detection verification |
|
University of Southern California |
Securing Agentic AI: From Local Detection to Global Assurance |
Automated Reasoning
Recipient |
University |
Research title |
Carnegie Mellon University |
A Visual Debugger for Program Verification |
|
Imperial College London |
SOLAR: Symbolic Learning for Automated Requirements Consistency |
|
University of Verona |
New Data Structure Theories and Quantifiers in CDSAT |
|
University of California Los Angeles |
Breaking the Parallelism Limit with SAT-solving Accelerators |
|
The University of Manchester |
Combining Formal Methods with Large Language Models in ESBMC: Enabling Automated Program Verification through AI/ML |
|
University of Waterloo |
Strata-Sphere: Expressive Type Systems and Language Formalizations |
|
TU Wien |
PASSAT: Improved Passing of Assertion Stacks to SAT in Incremental SMT Solvers |
|
University of California San Diego |
Evaluating and Improving Quantitative Reasoning in LLM Agents Using Sandbox Coding Tasks and Formal Tools |
|
The University of Texas at Austin |
Documenting and Recommending Tactics in HOL Light |
|
Columbia University in the City of New York |
Scaling Formal Verification of Security Properties for Unmodified System Software |
|
University of Maryland Baltimore County |
Autoformalization for Scientific Computing in Lean |
|
The University of Texas at Austin |
Documenting and Recommending Tactics in HOL Light |
|
North Carolina State University |
Neurosymbolic LLM Reasoning with Symbolical Soundness and Logical Consistency |
|
Imperial College London |
Soteria in Lean: Mechanising the Next Generation of Symbolic Execution Tools |
|
Karlsruhe Institute of Technology |
Resource-Efficient Flexible SAT Solving in HPC and Cloud Environments |
|
National University of Singapore |
Linear Types for a Foundational Multi-Modal Program Verifier |
|
University of Cambridge |
Gradual Lightweight Methods for High-Assurance Cloud Infrastructure |
|
Syracuse University |
Non-Markovian Agentic Meta-Reasoning |
|
Massachusetts Institute of Technology |
Synthesizing Library Models for Static Analysis via LLMs and Conformance Testing |
|
Harvard University |
Translating Formal Proofs of Differential Privacy via LLMs |
|
Massachusetts Institute of Technology |
Verifying Rust distributed system implementations using monotonic ownership state machines in Verus |
|
Boston University |
Auto-Formalization and Informalization through Two-Stage Reinforcement Learning |
|
Purdue University |
Scaling Interprocedural Data-Flow Analysis with LLMs |
AWS Agentic AI
Recipient |
University |
Research title |
Johns Hopkins University |
Multi-Party Differential Privacy: Unlocking Enterprise Agentic AI |
|
Worcester Polytechnic Institute |
Autonomous Catalyst Design with Agentic AI for Hydrogen Production |
|
University of California Davis |
FlowGuard: Evolutionary Red-Teaming for Safe Multimodal Web Agents |
|
University of California Santa Cruz |
CAMEO: Confidential Agentic Multi-component Enclave Orchestration |
|
University of Minnesota Twin Cities |
End-to-End Agentic AI for Scalable Chiplet Design with Extreme Parallelism and Heterogeneity |
|
Ben-Gurion University of the Negev |
Multi-Agent Pathfinding with Unassigned Agents |
|
The University of Texas at Austin |
From Observation to Intervention: Counterfactual Multi-Agent World Models for Autonomous Driving |
|
The University of Tennessee-Knoxville |
Beyond Walls of Text: Building UI-Native LLM Agents as the Next Gateway to the Internet |
|
University of Illinois at Urbana-Champaign |
Reinforcing Coordination: Streaming, Exploration, and Distillation for Long-Horizon Agent Learning |
|
Johns Hopkins University |
A Protocol Stack for Resource-Bound Multi-Agent AI |
|
University of Michigan |
Automating Large Scale Deployment of Infrastructure-based Safety Critical Event Detection with Agentic AI |
|
National University of Singapore |
Self-Configurable Agentic Learning via Co-optimization |
|
Johns Hopkins University |
Markov Near-Potential Function Based MARL Training for Mixed Cooperative–Competitive Agentic AI |
|
Texas A&M University |
A Retrieval-Augmented Dual-Attention Vision Framework for Standards-Aligned Infrastructure Inspection |
|
New York University Abu Dhabi |
AVAAS – Automated Vulnerability Analysis Through Advanced Agentic Systems |
|
Ben-Gurion University of the Negev |
Multi-Agent Pathfinding with Unassigned Agents |
|
Texas A&M University |
FlowGuard: Evolutionary Red-Teaming for Safe Multimodal Web Agents |
|
University of Michigan |
Benchmarking and Monitoring Multi-Agent Scheming |
|
Rice University |
Empowering Multimodal AI Agents with Continuous Learning |
|
University of Massachusetts Amherst |
A Framework for Proactive and Collaborative AI Agents |
|
University of Minnesota Twin Cities |
End-to-End Agentic AI for Scalable Chiplet Design with Extreme Parallelism and Heterogeneity |
|
University of Waterloo |
KNOWLEDGESTORE: A Dynamic Hierarchical Memory for Scalable, Enterprise-Ready AI Agents on AWS |
AWS Cryptography
Recipient |
University |
Research title |
The University of Sydney |
Efficient Robust Post-Quantum Distributed Key Generation and Threshold Signatures |
|
University of Illinois at Chicago |
Formally verified symmetric cryptography |
|
Purdue University |
Stronger Memory Hard Functions to Protect Passwords against Brute Force Attacks |
|
Paris Cité University |
Pseudorandom Correlations for Threshold Cryptography |
|
New York University |
Machine Unlearning and Computational Assumptions for AI |
|
Northeastern University - United States of America |
Practical Watermarking for LLMs via Pseduorandom Codes |
|
Massachusetts Institute of Technology |
Enhancing AI Safety Using Cryptography |
|
Boston University |
Pushing secure MPC beyond niche applications |
|
University of California Los Angeles |
Towards Low-Latency Maliciously Secure MPC for LLMs |
|
Royal Holloway - University of London |
New Approaches for the Linear Transform in BFV/BGV |
|
Carnegie Mellon University |
Practical Secure Computation At Scale |
|
University of Toronto |
Simultaneous-Message and Succinct Secure Computation |
|
University of Waterloo |
FantASM: Fast, Auditable, and Neat Assembly |
|
Arizona State University |
Fuzzy Secure Computation for Real-World Noisy Data |
|
Northwestern University - United States of America |
From Signing to Garbling: Exploring the Spectrum of Post-Quantum Primitives |
|
Stanford University |
Algorithms for Post-Quantum Cryptography |
|
National University of Singapore |
Practical Watermarking for LLMs via Pseduorandom Codes |
|
Georgia Institute of Technology |
Fuzzy Secure Computation for Real-World Noisy Data |
Cybersecurity and Anti-Abuse Technologies
Recipient |
University |
Research title |
University of California San Diego |
Detecting Anti-detect Browsers at Scale |
Devices Sustainability
Recipient |
University |
Research title |
Cornell University |
Agent-Driven Life Cycle Carbon Optimization for Sustainable Edge Devices |
|
Brown University |
Integrating Sustainability Reasoning into Early-Stage Electronics Design |
Amazon Research Awards team
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