In March 2021, Amazon notified applicants that they were recipients of the 2020 Amazon Research Awards, a program that provides unrestricted funds and AWS Promotional Credits to academic researchers investigating research topics across a number of disciplines.
Today, we’re publicly announcing the 100 award recipients who represent 59 universities in 13 countries. This round, ARA received a record number of submissions and funded nearly twice as many awards as the previous year. Each award is intended to support the work of one to two graduate students or postdoctoral students for one year, under the supervision of a faculty member.
ARA is funding awards under five call for proposals: AI for Information Security, Alexa Fairness in AI, AWS AI, AWS Automated Reasoning, and Robotics. Proposals were reviewed for the quality of their scientific content, their creativity, and their potential to impact both the research community, and society more generally. Theoretical advances, creative new ideas, and practical applications were all considered.
Recipients have access to more than 200 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.
“The 2020 Amazon Research Awards recipients represent a distinguished array of academic researchers who are pursuing research across areas such as ML algorithms and theory, fairness in AI, computer vision, natural language processing, edge computing, and medical research,” said Bratin Saha, vice president of AWS Machine Learning Services. “We are excited by the depth and breadth of their proposals, as well as the opportunity to advance the science through strengthened connections among academic researchers, their institutions, and our research teams.”
“As we enter into this golden age of robotics, we do so with our university partners. Not only are they shaping what is possible in robotics, they are inspiring many next- generation roboticists with their incredible creations and front-line teachings,” said Tye Brady, chief technologist for Amazon Robotics. “Our grant recipients are not only pursuing cutting-edge research that will benefit society, but perhaps more importantly are helping students from across the globe pursue a career in science and engineering.”
ARA funds proposals up to four 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.
Below is the list of 2020 award recipients, presented in alphabetical order.
Recipient |
University |
Research title |
Vikram Adve |
University of Illinois Urbana-Champaign |
Extending the LLVM compiler infrastructure for tensor architectures |
Pulkit Agrawal |
Massachusetts Institute of Technology |
A framework for multi-step planning for manipulating rigid objects |
Ron Alterovitz |
University of North Carolina at Chapel Hill |
Cloud-based motion planning: an enabling technology for next-generation autonomous robots |
Jimmy Ba |
University of Toronto |
Model-based reinforcement learning with causal world models |
Saurabh Bagchi |
Purdue University—West Lafayette |
Content and contention-aware approximate streaming video analytics for edge devices |
David Baker Effendi |
Stellenbosch University |
Dataflow analysis using code property graphs, graph databases and synchronized pushdown systems |
Sivaraman Balakrishnan |
Carnegie Mellon University |
Foundations of robust machine learning: from principled approaches to practice |
Elias Bareinboim |
Columbia University |
Off-policy evaluation through causal modeling |
Clark Barrett |
Stanford University |
Model-based testing of SMT solvers |
Lars Birkedal |
Aarhus University |
Modular reasoning about distributed systems: higher-order distributed separation logic |
David Blei |
Columbia University |
New directions in observational causal inference |
Eric Bodden |
Paderborn University |
HybridCG — dynamically-enriched call-Graph generation of Java enterprise applications |
Legand Burge |
Howard University |
Voice-FAQ: artificial intelligence for triaging cognitive decline through modeling vocal prosody and facial expressions |
James Caverlee |
Texas A&M University, College Station |
Fairness in recommendation without demographics |
Changyou Chen |
University at Buffalo |
Scaling up human-action analysis systems |
Danqi Chen |
Princeton University |
Building broad-coverage, structured dense knowledge bases for natural language processing tasks |
Helen Chen |
University of Waterloo |
Optimizing pretrained clinical embeddings for automatic COVID-related ICD coding |
Yiran Chen |
Duke University |
Privacy-preserving representation learning on graphs — a mutual information perspective |
Margarita Chli |
ETH Zurich |
Vision-based emergency landing in urban environments using reinforcement learning and deep learning |
Kyunghyun Cho |
New York University |
Independently controllable attributes for controllable neural text generation |
Carlo Ciliberto |
University College London |
Optimal transport for meta-learning |
Loris D’Antoni |
University of Wisconsin–Madison |
Correct-by-construction IAM policies |
David Danks |
Carnegie Mellon University |
An integrated framework for understanding human-AI hybrid decision-making |
Suhas Diggavi |
University of California, Los Angeles |
Compressed private and secure distributed edge learning |
Greg Durrett |
University of Texas At Austin |
Making conditional text generation fair and factual |
Sergio Escalera |
Universitat de Barcelona and Computer Vision Center |
Portable virtual try-on for smart devices |
Jan Faigl |
Czech Technical University in Prague |
Communication maps building in subterranean environments |
Pietro Ferrara |
Ca’ Foscari University of Venice |
IAM access control policies verification and inference |
Katerina Fragkiadaki |
Carnegie Mellon University |
Generalizing manipulation across objects, configurations and views using a visually-grounded library of behaviors |
Guillermo Gallego |
Technical University of Berlin |
Online in-hand object tracking and grasp failure detection with an event-based camera |
Grace Gao |
Stanford University |
Trustworthy autonomous vehicle localization using a joint model-driven and data-driven approach |
Stephanie Gil |
Harvard University |
Enabling the next generation of coordinated robots: scalable real-time decision making |
Luca Giuggioli |
University of Bristol |
Multi-robot online exploration in extreme unbounded environments through adaptive socio-spatial ordering |
Jorge Goncalves |
University of Melbourne |
Integrated qualification test framework to measure crowd worker quality and assign or recommend heterogeneous tasks |
Ananth Grama |
Purdue University—West Lafayette |
Scaling causal inference to explainable clinical recommendations |
Grace Gu |
University of California, Berkeley |
Surrogate machine learning model and quasi-static simulation of pneumatically actuated robotic devices |
Ronghui Gu |
Columbia University |
Microverification of the Linux KVM hypervisor: proving VM confidentiality and integrity |
Aarti Gupta |
Princeton University |
Learning abstract specifications from distributed program implementations |
Saurabh Gupta |
University of Illinois Urbana-Champaign |
Self-supervised discovery of object states and transitions from unlabeled videos |
Daniel Harabor |
Monash University |
Anytime constraint-based multi-agent pathfinding |
Hynek Hermansky |
Johns Hopkins University |
Multistream lifelong federated learning for machine recognition of speech |
Bin Hu |
University of Illinois Urbana-Champaign |
Provably robust adversarial reinforcement learning for sequential decision making in safety-critical environments |
Lifu Huang |
Virginia Tech |
Event-centric temporal and causal knowledge acquisition and generalization for natural language understanding |
Dinesh Jayaraman |
University of Pennsylvania |
Learning modular dynamics models for plug-and-play visual control |
Sven Koenig |
University of Southern California |
Improving planning and plan execution for warehouse automation |
Laura Kovacs |
TU Wien |
FOREST: first-order reasoning for ensuring system security |
Arun Kumar |
University of California, San Diego |
Improving automated feature type inference for AutoML on tabular data |
Himabindu Lakkaraju |
Harvard University |
Towards reliable and robust model explanations |
Kevin Leyton-Brown |
University of British Columbia |
Automated machine learning for tabular datasets using hyperband embedded reinforcement learning |
Bo Li |
University of Illinois Urbana-Champaign |
Machine learning evaluation as a service for robustness, fairness, and privacy utilities |
Ke Li |
University of Exeter |
Many hands make work light: multi-task deep semantic learning for testing web application firewalls |
Zhiqiang Lin |
Ohio State University |
Type-aware recovery of symbol names in binary code: a machine learning based approach |
Jeffrey Liu |
Massachusetts Institute of Technology |
Integrating the low altitude disaster imagery (LADI) dataset into the MIT Beaver Works curriculum |
Michael Mahoney |
University of California, Berkeley |
Systematic methods for efficient inference and training of neural networks |
Radu Marculescu |
University of Texas |
New directions for 3D object detection: distributed inference on edge devices using knowledge distillation |
Ruben Martins |
Carnegie Mellon University |
Improving performance and trust of MaxSAT solvers |
Jiri Matas |
Czech Technical University in Prague |
Training neural networks on non-differentiable losses |
Michael Milford |
Queensland University of Technology |
Complementarity-aware multi-process fusion for long term localization |
Heather Miller |
Carnegie Mellon University |
Directed automated explicit-state model checking for distributed applications |
Ndapa Nakashole |
University of California, San Diego |
Learning representations for voice-based conversational agents for older adults |
Shrikanth Narayanan |
University of Southern California |
Toward inclusive human-AI conversational experiences for children |
Lerrel Pinto |
New York University |
Learning to manipulate deformable objects through robust simulations |
Ravi Ramamoorthi |
University of California, San Diego |
Sparse multi-view object acquisition using learned volumetric representations |
Philip Resnik |
University of Maryland, College Park |
Advanced topic modeling to support the understanding of COVID-19 and its effects |
Daniela Rus |
Massachusetts Institute of Technology |
Learning to plan through imagined self-play for multi-agent system |
Supreeth Shashikumar |
University of California, San Diego |
Privacy preserving continual learning with applications to critical care |
Robert Shepherd |
Cornell University |
Enduring and adaptive robots via electrochemical blood |
Cong Shi |
University of Michigan, Ann Arbor |
Machine learning for personalized assortment optimization |
Florian Shkurti |
University of Toronto |
Generating physically realizable adversarial driving scenarios via differentiable physics and rendering simulators |
Abhinav Shrivastava |
University of Maryland, College Park |
The pursuit of knowledge: discovering and localizing new concepts using dual memory |
Roland Siegwart |
ETH Zurich |
Safe self-calibration of hybrid aerial vehicles |
Sameer Singh |
University of California, Irvine |
Detecting and fixing vulnerabilities in NLP models via semantic perturbations and tracing data influence |
Noah Smith |
University of Washington - Seattle |
Language model customization |
Mahdi Soltanolkotabi |
University of Southern California |
Artificial intelligence for fast and portable medical imaging (with limited training data) |
Seung Woo Son |
University of Massachusetts Lowell |
Reliable and accurate anomaly detection in edge nodes using sparsity profile |
Dawn Song |
University of California, Berkeley |
Knowledge-enhanced cyber threat hunting |
Dezhen Song |
Texas A&M University, College Station |
Optoacoustic material and structure pretouch sensing at robot fingertip |
Shuran Song |
Columbia University |
Dexterity through diversity:learning a generalizable grasping policy for diverse end-effectors |
Yizhou Sun |
University of California, Los Angeles |
Accelerating graph neural network training |
Russ Tedrake |
Massachusetts Institute of Technology |
Intuitive physics for manipulation |
James Tompkin |
Brown University |
Real-time multi-camera fusion for unoccluded VR robot teleoperation |
Emina Torlak |
University of Washington - Seattle |
Automated verification of JIT compilers for BPF |
Marynel Vazquez |
Yale University |
Evaluating social robot navigation via online human-driven simulations |
Nisheeth Vishnoi |
Yale University |
Fair and error-resilient algorithms for AI and ML |
Gang Wang |
University of Illinois at Urbana–Champaign |
Combating concept drift in security applications via proactive data synthesis |
Hao Wang |
Rutgers University-New Brunswick |
Structured domain adaptation with applications to personalization and forecasting |
James Wang |
Pennsylvania State University |
Affective and social interaction between human and intelligent machine |
Gloria Washington |
Howard University |
Towards identification of uncomfortable speech in conversations |
Chuan Wu |
The University of Hong Kong |
Compilation optimization in distributed DNN training: joining OP and tensor fusion/partition |
Eugene Wu |
Columbia University |
Human-in-the-loop data debugging for ML-oriented analytics |
Jiajun Wu |
Stanford University |
Implicit dynamic scene representation learning for robotics |
Ming-Ru Wu |
Dana-Farber Cancer Institute |
From bench to clinic – machine-learning based cancer immunotherapy design |
Diyi Yang |
Georgia Institute of Technology |
Abstractive conversation summarization at scale |
Sixian You |
Massachusetts Institute of Technology |
AI-driven label-free histology for cancer diagnosis |
Jingjin Yu |
Rutgers University-New Brunswick |
Pushing the limits of efficient and optimal multi-agent path finding through exploring space utilization optimization and adaptive planning horizon heuristics |
Rui Zhang |
Pennsylvania State University |
Building robust conversational question answering systems over databases of tabular data |
Yu Zhang |
University of South Florida |
Design of an automated advanced air mobility flight planning system (AAFPS) |
Yuke Zhu |
University of Texas at Austin |
Learning implicit shape affordance for grasping and manipulation |
Marinka Zitnik |
Harvard University |
Actionable graph learning for finding cures for emerging diseases |
James Zou |
Stanford University |
How to make AI forget you? Efficiently removing individuals’ data from machine learning models |
