We have an opening for postdoctoral scholar(s) for AI (computer vision and machine learning) and Healthcare. For more information and to apply, see here.

Arnold Milstein, M.D., M.P.H.
Professor of Medicine
Director, CERC
Jeffrey Jopling, M.D.
Research Fellow, CERC
Meghan Ramsey, M.D.
Research Fellow, CERC
Kelly Vranas, M.D.
Research Fellow, CERC
Beatrice Podtschaske, Ph.D.
Visiting Scholar, CERC
Pilot Projects
Intelligent Hand Hygiene Support
@ Lucile Packard Children's Hospital at Stanford
Reliable use of hand hygiene is associated with large reductions in hospital-acquired infections, which account for a significant fraction of hospital complications, mortality and healthcare expenditures. We are designing and demonstrating privacy-protective depth sensors and refining computer vision technology to make it easier for all clinicians and staff to perfect hand hygiene.
Intelligent ICU Clinical Pathway Support
@ Stanford Hospital and Clinics
@ Intermountain Healthcare
ICU patient monitoring by trained personnel is costly and time-consuming. Working with colleagues at Stanford's adult hospital and Intermountain Healthcare, we will apply and refine computer vision technology in the ICU to make it easier for clinicians to continuously identify opportunities to detect and respond to changes in patients' health status including patient alertness and pain. Our goal is to reduce clinicians' monitoring workload and speed patients' recovery.
Intelligent Senior Wellbeing Support
@ Palo Alto Medical Foundation
@ On Lok Senior Health Services
@ Intermountain Healthcare
We are designing and will demonstrate an integrated solution for the remote monitoring, assessment and support of seniors living independently at home. Our objective is to improve the speed and reliability of health risk detection and support timely, personalized intervention. We will investigate the use of multiple sensors for the detection and recording of daily activities, lifestyle patterns, emotions, and vital signs, as well as the development of intelligent mechanisms for translating multi-sensor inputs into accurate situational assessment and rapid response. Our goal is to allow seniors to extend their capacity to live at home, improve their quality of life and avoid unnecessary and costly relocations into institutional care. We aim to advance the understanding of how sensor-detected behavioral and cognitive cues correlate with meaningful fluctuations in health status.