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2019 Seed Grant Recipients

The Seed Research Grants are designed to support new, ambitious, and speculative ideas with the objective of getting initial results.

Artificial Intelligence for Scientific Discovery

Susan Athey, David Hirshberg, Guido Imbens, Stefan Wager

A Causal Decision-Learning Approach for Identifying Cost-Effective Clinical Pathways

Mohsen Bayati, Merle Ederhof, James Martin, Alex Chin, Jeffrey Jopling

Virtual Multisensory Interaction: From Robots to Humans

Jeannette Bohg, Allison Okamura, Doug James 

Statistical Machine Learning for Understanding and Improving Social Mobility Among the Poor: A Precision Approach to Intervention

Emma Brunskill, Geoff Cohen

Understanding and Addressing Ethical Challenges with Implementation of Machine Learning to Advance Palliative Care

Danton Char, Henry Greely, Nigam Shah

Administering by Algorithm: Artificial Intelligence in the Regulatory State

David Freeman, Dan Ho, Tino Cuellar

RoboIterum: An Augmented Reality Interface for Iterative Design of Situated Interactions with Intelligent Robots

Sean Follmer, James Landay, Parastoo Abtahi

Urbanization at the Margins: Edges & Seams in the Global South

Roz Naylor, Zephyr Frank, Erik Steiner, Deland Chan, Leonardo Barleta

Deep Neural Network for Real-Time EEG Decoding of Musical Rhythm Imagery: Towards a Brain-Computer Interface Application for Stroke Rehabilitation

Takako Fujioka, Irán Román, Jay McClelland

Multi-modal Inference in Brains, Minds, and Machines

Tobias Gerstenberg, Justin Gardner, Hyo Gweon, Scott W. Linderman

Video-based Real Time Monitoring of Respiratory Conditions in the Pediatric Emergency Department

Sumit Bhargava, Dan Imler, Peyton Greenside, Karan Goel

Learning to Play: Understanding Infant Development with Intrinsically Motivated Artificial Agents

Daniel LK Yamins, Fei-Fei Li, Mike Frank, Nick Haber, Damian Mrowca, Stephanie Wang, Kun Ho Kim, Eli Wang, Bria Long, Judy Fan, George Kachergis, Hyo Gweon

Folk Theories of AI Systems: An Approach for Developing Interpretable AI

Jeffrey Hancock, Michael Bernstein, Sunny Liu, Danae Metaxa

“Personality Design” in Artificial Intelligence-enabled Robots, Conversational Agents and Virtual Assistants

Pamela Hinds, Angele Christine, Prachee Jain

Using AI to Safeguard Our Drinking Water

Kate Maher, Jef Caers, Bill Mitch, James Dennedy-Frank

Predicting Learning Outcomes with Machine Teachers

Roy Pea, Bethanie Maples

Developing a Computational Approach for Identifying Characteristics of Psychotherapy

Bruce Arnow, Stewart Agras, Nigam Shah, Fei-Fei Li, Adam Miner, Albert Haque, Michelle Guo

Crowdsourcing Concept Art: An Art Style Classifier to Maintain Consistent Artistic Vision at Scale

Michael Bernstein, Camille Utterback

Modeling Finger Sense Training and Math Learning in Children

Allison Okamura, Jo Boaler, Dorsa Sadigh, Melisa Orta Martinez, Julie Walker, Margaret Koehler

PopBots: An Army of Conversational Agents for Daily Stress Management

Dan Jurafsky, Pablo E. Paredes

Opportunistic Screening for Coronary Artery Disease Using Artificial Intelligence

David Maron, Alex Sandhu, Fatima Rodriguez, Bhavik Patel, Matthew Lungren, Curtis Langlotz, Christopher Chute, Pranav Rajpurkar

Promoting Well-Being by Predicting Behavioral Vulnerability in Real-Time

Jeffrey Hancock, Gabriella Harani, Jure Leskovec, Adam Miner, Róbert Pálovics, Katie Roehrick

Using Artificial Intelligence to Optimize Patient Mobility and Functional Outcomes

Arnold Milstein, Fei-Fei Li, Francesca Rinaldo Salipur, Bingbin Liu


Predicting Malaria Outbreaks: AI to Learn, Classify and Predict Across Diverse Paleo-demographic, Climatic and Genomic Data

Krish Seetah, Robert Dunbar, Carlos Bustamante, Giulio De Leo, Erin Mordecai, Michelle Barry, Bright Zhou, David Pickel, Hannah Moots

Robust Deep Neural Network Optimization with Second Order Method for Biomedical Applications

Stephen Boyd, Mohsen Bayati, Lei Xing, Varun Vasudevan, Kate Horst

The Economic Consequences of Artificial Intelligence

Nick Bloom, Matt Gentzkow, Pete Klenow, Caroline Hoxby, Tim Bresnahan, Michael Webb

Uncovering gender inequalities in East Africa: Using AI to gain insights from media data

Gary Darmstadt, James Zou, Londa Schiebinger, Ann Weber, Valerie Meausoone

Developing Artificial Intelligence Tools for Dynamic Cancer Treatment Strategies

Daniel Rubin, Michael Gensheimer, Susan Athey, Ross Shachter, Jiaming Zeng

Want out? Removing Individuals’ Data from Machine Learning Models

James Zou, Greg Valiant, Amy Motomura