David S. Hayden

PhD Candidate
Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology

Office: 32-D475a
Address: 32 Vassar St., Cambridge, MA 02142
Email: dshayden [at] mit [dot] edu
CV

Research

I build probabilistic models that enable large-scale hypothesis testing in behavioral science with a minimum of human oversight. By working towards automated interventions, my tools will make new experimental designs possible from what once were observational studies.

Broadly, my research interests are in interpretable machine learning and computer vision, with special focus on Bayesian nonparametrics applied to time-series, distributions on manifolds and using uncertainty to guide decision making, analysis and experimental design.

News

Publications

Sequential Bayesian Experimental Design with Variable Cost Structure
Sue Zheng, David S. Hayden, Jason Pacheco, John W. Fisher III
Neurips 2020
Paper Supplemental

Nonparametric Object and Parts Modeling with Lie Group Dynamics
David S. Hayden, Jason Pacheco, John W. Fisher III
CVPR 2020
Paper Supplemental Video Code

Atypical Behaviour and Connectivity in SHANK3-Mutant Macaques
Yang Zhou, Jitendra Sharma, Qiong Ke, Rogier Landman, Jingli Yuan, Hong Chen, David S. Hayden et al.
Nature, June 2019
Paper

Unobtrusive, Wearable Social Interaction Detection and Assistance
David S. Hayden, Robert C. Miller, Seth Teller
CHI 2014 Workshop on Assistive Augmentation
Paper

The Accuracy-Obtrusiveness Tradeoff for Wearable Vision Platforms
David S. Hayden, Carl Vondrick, Stella Jia, Yafim Landa, Robert C. Miller, Antonio Torralba, Seth Teller
CVPR 2012 Workshop on Egocentric Vision
Paper

Using Clustering and Metric Learning to Improve Science Return of Remote Sensed Imagery
David S. Hayden, Steve Chien, David R. Thompson, Rebecca CastaƱo
ACM Transactions on Intelligent Systems and Technology 2012
Paper

Note-Taker 3.0: an Assistive Technology Enabling Students who are Legally Blind to Take Notes in Class
David S. Hayden, Michael Astrauskas, Qian Yan, Liqing Zhou, John A. Black Jr.
ASSETS 2011
Paper

The Note-Taker: a Tablet PC Based Device that Helps Students Take and Review Classroom Notes
David S. Hayden, Liqing Zhou, John A. Black Jr.
The Impact of Tablet PCs and Pen-based Technology on Education (2010, ISBN: 1557535744)
Paper

Note-Taker 2.0: the Next Step Toward Enabling Students who are Legally Blind to Take Notes in Class
David S. Hayden, Liqing Zhou, Michael Astrauskas, John A. Black Jr.
ASSETS 2010
Paper

Note-Taker: Enabling Students who are Legally Blind to Take Notes in Class
David S. Hayden, Dirk Colbry, John A. Black Jr., Sethuraman Panchanathan
ASSETS 2008
Paper