The increasing adoption of mobile health (mHealth) technology has created an unprecedented opportunity to address key challenges facing the US healthcare system to improve health outcomes and reduce the cost of care, particularly for patients with chronic conditions such as diabetes and heart failure. mHealth technologies provide a means to measure health-related variables from a patient’s daily life environment and deliver health-related messaging, motivation, and other forms of intervention to patients in real-time. Via this feedback loop, patients can be given new tools for achieving their health-related goals while working more effectively with care-providers. Additionally, insights into the structural barriers to health improvements, such as a lack of safe and accessible recreational areas, can be obtained to inform community development and public policy. Moreover, these technologies can improve access to care for rural populations, by allowing care providers to assay a patient’s health status without inpatient visits or nursing outcall. Achieving these goals requires advances in multiple research areas, including (but not limited to):
- Machine learning methods that can leverage high volume streaming sensor data to infer states of health and behavior,
- Novel adaptive intervention designs that can deliver just-in-time feedback and motivation,
- Control systems modeling and optimization approaches for such real-time interventions,
- Artificial intelligence and data mining approaches to extracting risk factors for health and disease from clinical databases (e.g., electronic health records) and longitudinal cohort studies,
- Human-computer interaction and human factors research in developing solutions via participatory design while addressing ethical and privacy concerns.
In order to tackle these challenges, UIUC will hire a cluster of four new faculty in the broadly themed area of AI for Community Health. This cluster hire will catalyze the growth of health research at UIUC with a focus on sensor-based interventions to tackle chronic health conditions. The cluster will be supported by multiple research centers which will provide resources and support to develop this important research area. Participating centers include the Health Care Engineering Systems Center (HCESC) in the Grainger College of Engineering, the Center on Aging, Health, and Disability (CHAD) in the College of Applied Health Sciences, and the National Center for Supercomputing Applications (NCSA), among others.
Interested faculty candidates should apply for a position in one of the four participating units listed below. Your cover letter should state your interest in being considered for the AI for Community Health cluster hire. An application portal for each department with a description of the open positions and the application requirements will be shared soon.
Participating Units in the AI for Community Health cluster:
- Grainger College of Engineering
o Department of Computer Science (Link to application portal forthcoming)
o Department of Industrial and Enterprise Systems Engineering (Link to application portal forthcoming)
- College of Applied Health Sciences
o Department of Kinesiology and Community Health (Link to application portal forthcoming)
o Department of Recreation, Sport, and Tourism (Link to application portal forthcoming)
Please contact firstname.lastname@example.org for any questions related to the AI for Community Health cluster hire program.