75 citations · 82 across the 7 of their papers we have counts for
7 papers
Reinforcement learning
Sarod Yatawatta
Observing celestial objects and advancing our scientific knowledge about them involves tedious planning, scheduling, data collection and data post-processing. Many of these operati…
brainlife.io: A decentralized and open source cloud platform to support neuroscience research
Soichi Hayashi, Bradley A. Caron, Anibal Sólon Heinsfeld +61
Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the comple…
Gaussian Latent Dirichlet Allocation for Discrete Human State Discovery
Congyu Wu, Aaron Fisher, David Schnyer
In this article we propose and validate an unsupervised probabilistic model, Gaussian Latent Dirichlet Allocation (GLDA), for the problem of discrete state discovery from repeated,…
Exploring Post COVID-19 Outbreak Intradaily Mobility Pattern Change in College Students: a GPS-focused Smartphone Sensing Study
Congyu Wu, Hagen Fritz, Cameron Craddock +3
With the outbreak of the COVID-19 pandemic in 2020, most colleges and universities move to restrict campus activities, reduce indoor gatherings and move instruction online. These c…
Circadian Rhythms are Not Captured Equal: Exploring Circadian Metrics Extracted by Different Computational Methods from Smartphone Accelerometer and GPS Sensors in Daily Life Tracking
Congyu Wu, Megan McMahon, Hagen Fritz +1
Circadian rhythm is the natural biological cycle manifested in human daily routines. A regular and stable rhythm is found to be correlated with good physical and mental health. Wit…
Improving Prediction of Real-Time Loneliness and Companionship Type Using Geosocial Features of Personal Smartphone Data
Congyu Wu, Amanda N. Barczyk, R. Cameron Craddock +6
Loneliness is a widely affecting mental health symptom and can be mediated by and co-vary with patterns of social exposure. Using momentary survey and smartphone sensing data colle…
Multi-Modal Data Collection for Measuring Health, Behavior, and Living Environment of Large-Scale Participant Cohorts: Conceptual Framework and Findings from Deployments
Congyu Wu, Hagen Fritz, Zoltan Nagy +10
As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented c…