Our work in pervasive sensing enables novel ways to accelerate observational analysis by employing multi-modal pattern recognition capabilities to pre-segment and tag records, and thus increase analysis power by visualizing multimodal activity and macro-micro relationships. We are combining these approaches to highlight behavioral data through interactive data visualization aimed at uncovering hidden pattern and allow researchers to investigate new research questions.
In our research we are expanding our work on visualizing and analyzing multimodal activity dynamics with tools based on interactive web-based visualization that allow researcher to analyze a variety of different multi-dimensional data.
In general this research has the potential to enable exploration of critical new insights in terms of multi-dimensional data for public health and we are actively and continuously exploring those possibilities to provide researchers with innovative tools to analyze multimodal data and uncover hidden patterns.
Exploratory Data Analysis
We are employing cutting-edge visualization library to create effective tools to explore rich datasets in the healthcare domain. The goal is to enable data-driven approaches to generate insights into multidimensional data, and then drive specific questions and more traditional hypothesis-driven research.
|Molecular epidemiology for HIV prevention for drug users and other risk groups
(NIH/NIDA Avantgarde – September 2012 – August 2017)
|A Multiscale Framework for Analyzing Activity Dynamics
(US NSF IIS-0729013, October 2009 – August 2011)
|Flight Crew Performance Data Collection and Analysis Tool
(UCSD – Boeing Project Agreement 2011/2012, January 2011 – September 2012)
Social Network Analysis and Visualization
Important behavioral dynamics are emerging from social media and understanding the network characteristics of the people involved is key to inform potential interventions. We are developing novel ways to understand network data, especially in the context of social media and health.
|Characterizing the Relationship of METH Use and Neurocognitive Impairment in HIV At-risk Online Networks
(TMARC Pilot PST7TP2/2016, Translational Methamphetamine AIDS Research Center, March 2016 – February 2018)
Multimodal Tools and Simulators
We are building tools for a variety of healthcare professionals who need smarter tools to help them, and their stakeholders (patients, fellow clinicians) to better access and explore their data, as well as make decisions based on them. Projects range the field of HIV/AIDS, as well as Nephrology.
|PIRC: Primary Infection Resource Consortium
(NIH/NIAID, Aug 2013 – July 2017)
Multimodal Learning Analytics
Learning Analytics research, focuses on computer-based learning contexts, where tools automatically capture, in a fine-grained level of detail, the interactions across users. The relative abundance of readily available data and the low technical barriers to process it, make computer-based learning systems possible
Publications – Multimodal Exploratory Data Analysis and Visualization