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Prior Seed Grant Recipients

2019 HAI Seed Grant Recipients

Artificial Intelligence for Scientific Discovery

  • Susan Athey (Business)
  • David Hirshberg (Economics)
  • Guido Imbens (Business, Economics)
  • Stefan Wager (Business)

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

  • Mohsen Bayati (Business)
  • Merle Ederhof (CERC)
  • James Martin (Stanford Health Care)
  • Alex Chin (Radiation Oncology)
  • Jeffrey Jopling (Surgery)

Virtual Multisensory Interaction: From Robots to Humans

  • Jeannette Bohg (Computer Science)
  • Allison Okamura (Mechanical Engineering)
  • Doug James (Computer Science)

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

  • Emma Brunskill (Computer Science)
  • Geoff Cohen (Education)

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

  • Danton Char (Anesthesiology)
  • Henry Greely (Law)
  • Nigam Shah (Medicine, Biomedical Data Science)

Administering by Algorithm: Artificial Intelligence in the Regulatory State

  • David Freeman Engstrom (Law)
  • Dan Ho (Law)
  • Tino Cuellar (Law)

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

  • Sean Follmer (Mechanical Engineering)
  • James Landay (Computer Science)
  • Parastoo Abtahi (Computer Science)

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

  • Roz Naylor (Earth System Science)
  • Zephyr Frank (History)
  • Erik Steiner (Spatial History Project)
  • Deland Chan (H&S)
  • Leonardo Barleta (History)

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

  • Takako Fujioka (Music)
  • Irán Román (Music, Neuroscience)
  • Jay McClelland (Psychology)

Multi-modal Inference in Brains, Minds, and Machines

  • Tobias Gerstenberg (Psychology)
  • Justin Gardner (Psychology)
  • Hyo Gweon (Psychology)
  • Scott W. Linderman (Statistics, Neuroscience)

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

  • Sumit Bhargava (Pediatrics)
  • Dan Imler (Emergency Medicine)
  • Peyton Greenside (Computer Science)
  • Karan Goel (Computer Science)

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

  • Daniel LK Yamins (Psychology)
  • Fei-Fei Li (Computer Science)
  • Mike Frank (Psychology)
  • Nick Haber (Psychology)
  • Damian Mrowca (Computer Science)
  • Stephanie Wang (Computer Science)
  • Kun Ho Kim (Computer Science)
  • Eli Wang (Electrical Engineering)
  • Bria Long (Psychology)
  • Judy Fan (Psychology)
  • George Kachergis (Psychology)
  • Hyo Gweon (Psychology)

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

  • Jeffrey Hancock (Communication)
  • Michael Bernstein (Computer Science)
  • Sunny Liu (Communication)
  • Danae Metaxa (Computer Science)

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

  • Pamela Hinds (Management Science and Engineering)
  • Angele Christine (Communication)
  • Prachee Jain (Management Science and Engineering)

Using AI to Safeguard Our Drinking Water

  • Kate Maher (Earth System Science)

  • Jef Caers (Geological Sciences)

  • Bill Mitch (Civil and Environmental Engineering)

  • James Dennedy-Frank (Biology)

Predicting Learning Outcomes with Machine Teachers

  • Roy Pea (Education), Emma Brunskill (Computer Science), Bethanie Maples (Computer Science), Joyce He (Education)

Developing a Computational Approach for Identifying Characteristics of Psychotherapy

  • Bruce Arnow (Psychiatry and Behavioral Sciences)

  • Stewart Agras (Psychiatry and Behavioral Sciences)

  • Nigam Shah (Medicine, Biomedical Data Science)

  • Fei-Fei Li (Computer Science)

  • Adam Miner (Psychiatry and Behavioral Sciences)

  • Albert Haque (Computer Science)

  • Michelle Guo (Computer Science)

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

  • Michael Bernstein (Computer Science)

  • Camille Utterback (Art and Art History)

Modeling Finger Sense Training and Math Learning in Children

  • Allison Okamura (Mechanical Engineering)

  • Jo Boaler (Education)

  • Dorsa Sadigh (Computer Science, Electrical Engineering)

  • Melisa Orta Martinez (Mechanical Engineering)

  • Julie Walker (Mechanical Engineering)

  • Margaret Koehler (Mechanical Engineering)

PopBots: An Army of Conversational Agents for Daily Stress Management

  • Dan Jurafsky (Computer Science, Linguistics)

  • Pablo E. Paredes (Radiology, Psychiatry and Behavioral Sciences)

Opportunistic Screening for Coronary Artery Disease Using Artificial Intelligence

  • David Maron (Cardiovascular Medicine)

  • Alex Sandhu (Cardiovascular Medicine)

  • Fatima Rodriguez (Cardiovascular Medicine)

  • Bhavik Patel (Radiology)

  • Matthew Lungren (Radiology)

  • Curtis Langlotz (Radiology)

  • Christopher Chute (Computer Science)

  • Pranav Rajpurkar (Computer Science)

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

  • Jeffrey Hancock (Communication)

  • Gabriella Harani (Communication)

  • Jure Leskovec (Computer Science)

  • Adam Miner (Psychiatry and Behavioral Sciences)

  • Róbert Pálovics (Computer Science)

  • Katie Roehrick (Communication)

Using Artificial Intelligence to Optimize Patient Mobility and Functional Outcomes

  • Arnold Milstein (Medicine)

  • Fei-Fei Li (Computer Science)

  • Francesca Rinaldo Salipur (CERC, General Surgery)

  • Bingbin Liu (Computer Science)

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

  • Krish Seetah (Anthropology)

  • Robert Dunbar (Earth System Science)

  • Carlos Bustamante (Biomedical Data Science, Genetics)

  • Giulio De Leo (Biology)

  • Erin Mordecai (Biology)

  • Michelle Barry (CIGH)

  • Bright Zhou (Medicine)

  • David Pickel (Classics)

  • Hannah Moots (Anthropology)

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

  • Stephen Boyd (Electrical Engineering)

  • Mohsen Bayati (Business)

  • Lei Xing (Radiation Oncology)

  • Varun Vasudevan (ICME)

  • Kate Horst (Radiation Oncology)

The Economic Consequences of Artificial Intelligence

  • Nick Bloom (Economics)

  • Matt Gentzkow (Economics)

  • Pete Klenow (Economics)

  • Caroline Hoxby (H&S, Hoover Institution, SIEPR)

  • Tim Bresnahan (Economics)

  • Michael Webb (Economics)

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

  • Gary Darmstadt (Pediatrics-Neonatology)

  • James Zou (Biomedical Data Science)

  • Londa Schiebinger (History)

  • Ann Weber (Pediatrics)

  • Valerie Meausoone (Population Health Sciences)

Developing Artificial Intelligence Tools for Dynamic Cancer Treatment Strategies

  • Daniel Rubin (Radiology, Biomedical Data Science)

  • Michael Gensheimer (Radiation Oncology)

  • Susan Athey (Business)

  • Ross Shachter (Management Science and Engineering)

  • Jiaming Zeng (Management Science and Engineering)

Want out? Removing Individuals’ Data from Machine Learning Models

  • James Zou (Biomedical Data Science)

  • Greg Valiant (Computer Science)

  • Amy Motomura (Law)

2018 HAI Seed Grant Recipients

Adversarial Examples for Humans?

  • Gregory Valiant

  • Noah Goodman

Automated Moderation of Small Group Deliberation

  • Ashish Goel

  • James Fishkin

“Always On” Genetic Patient Diagnosis

  • Gill Bejerano

  • Jon Bernstein

Correcting Gender and Ethnic Biases in AI Algorithms

  • James Zou

  • Londa Schiebinger

  • Serena Yeung

  • Carlos Bustamante

Dynamic Artificial Intelligence-Therapy for Autism on Google Glass

  • Dennis Wall

  • Tom Robinson

  • Terry Winograd

Enabling Natural-Language Interactions in Educational Software

  • Alex Kolchinski

  • Sherry Ruan

  • Dan Schwartz

  • Emma Brunskill

Fast, Multiphase Human-in-the-loop Optimization of Exoskeleton Assistance

  • Steven Collins

  • Emma Brunskill

Free Exploration in Human-Centered AI Systems

  • Mohsen Bayati

  • Ramesh Johari

Gender Bias in Conversations with Chatbots

  • Katie Roehrick

  • Jeff Hancock

  • Byron Reeves

  • Londa Schiebinger

  • James Zou

  • Garrick Fernandez

  • Debnil Sur

Harnessing AI to Answer Questions about Diversity and Creativity

  • Dan McFarland

  • Londa Schiebinger

  • James Zou

The Impact of Artificial Intelligence on Perceptions of Humanhood

  • Benoît Monin

  • Erik Santoro

The Impact on Society of Autonomous Mobile Robots: A Pilot Study

  • Marco Pavone

  • Mark Duggan

  • David Grusky

Improving Refugee Integration Through Data-Driven Algorithmic Assignment

  • Jens Hainmueller

  • Kirk Bansak

  • Andrea Dillon

  • Jeremy Ferwerda

  • Dominik Hangartner

  • Duncan Lawrence

  • Jeremy Weinstein

Learning Behavior Change Interventions At Scale

  • Michael Bernstein

  • James Landay

Learning Decision Rules with Complex, Observational Data

  • Xinkun Nie

  • Stefan Wager

Learning Haptic Feedback for Motion Guidance

  • Julie Walker

  • Andrea Zanette

  • Mykel Kochenderfer

  • Allison Okamura

Mining the Downstream Effects of Artificial Intelligence on How Clinicians Make Decisions

  • Ron Li

  • Jason Ku Wang

  • Lance Downing

  • Lisa Shieh

  • Christopher Sharp

  • Jonathan Chen

New Moral Economy in an Age of Artificial Intelligence

  • Margaret Levi

  • Justice Mariano-Florentino Cuellar

  • Roberta Katz

  • John Markoff

  • Jane Shaw

Novel Approach to Map Seasonal Changes in Infection Risk for Schistosomiasis: a Multi-Scale Integration of Satellite Data and Drone Imagery by Using Artificial Intelligence

  • Giulio De Leo

  • Susanne Sokolow

  • Eric Lambin

  • Zac YC Liu

  • Chris Re

  • I. Jones

  • R. Grewelle

  • A. Ratner

  • A. Lund

Planning for Multi-Modal Human-Robot Communication

  • Yuhang Che

  • Cara Nunez

  • Allison Okamura

  • Dorsa Sadigh

Scaling Collection of Labeled Data for Creating AI Systems through Observational Learning

  • Daniel Rubin

  • Chris Re

  • Jared Dunnmon

  • Alex Ratner

  • Darvin Yi

Smart Learning Healthcare System for Human Behavior Change

  • Michelle Guo

  • Fei-Fei Li

  • Arnold Milstein

Using AI to Facilitate Citizen Participation in Democratic Policy Deliberations

  • Deger Turan

  • Frank Fukuyama

  • Jerry Kaplan

  • Larry Diamond

  • Eileen Donahoe

  • Chris Potts

Using Computer Vision to Measure Neighborhood Variables Affecting Health

  • Jackelyn Huang

  • Nikhil Naik

Using Deep Learning for Imaging Alzheimer’s Disease with Simultaneous Ultra-low-dose PET/MRI

  • Greg Zaharchuck

  • Bill Dally

  • John Pauly

  • Elizabeth Mormino