I build probabilistic models that enable large-scale hypothesis testing
with a minimum of human oversight. By working towards automated
interventions, my tools will make new experiment designs possible from
what once were observational studies.
Broadly, I work on interpretable machine learning and vision with
focus on behavior analysis, multi-object tracking, Bayesian
nonparametrics applied to time-series, distributions on manifolds, and
using uncertainty to guide decision making, analysis, and experiment
design.
Uncertainty Quantification and Structure Discovery for Scalable Behavior Science
David S. Hayden (Advisor: John W. Fisher III, Comittee: Robert Desimone, Justin Solomon)
PhD Thesis 2021
Thesis
Sequential Bayesian Experimental Design with Variable Cost Structure
Sue Zheng, David S. Hayden, Jason Pacheco, John W. Fisher III
Neurips 2020
Paper
Supplemental
Efficient Data Association and Uncertainty Quantification for Multi-Object Tracking
David S. Hayden, Sue Zheng, John W. Fisher III
arXiv 2020
Paper
Code
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
Code
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