Forschungskolloquium Wirtschaftsinformatik

05. Mai

Im Rahmen des Forschungskolloquiums Wirtschaftsinformatik und Data Science referiert Herr Tauhidur Rahman, Assistant Professor in Computer Science an der Universität Massachusetts Amherst, über "Harnessing Early Syndromic Signals with Large-Scale Mobile Sensor Data for Personal and Population Health" via Zoom am 5. April 2022, ab 16:15 Uhr.

Abstract

Personal and population health applications built on top of large-scale mobile sensor data and computing platforms have a great potential to impact the way we diagnose diseases, track, and manage our health. However, the existing sensing mechanisms often fail to accurately capture and infer syndromic signatures that are indicative of anomalies in internal physiological and behavioral processes at an earlier stage. A mobile sensing system that can harness early syndromic signals at an individual or a community level can pave the way to effective just-in-moment intervention, early screening, and prevention.

In this talk, I will present our recent and ongoing research to demonstrate how on-body and off-body sensor systems can harness specific syndromic signals for modeling opioid addiction, preschool children psychopathology, and infectious diseases. I will describe how a physics-informed time series modeling approach can gain a more robust predictive intelligence for these syndromic signals. Finally, I will present a contactless sensing platform that can serendipitously capture syndromic signals from crowds in public spaces (e.g., hospital waiting rooms) for population-level Influenza-like Illness modeling.

Zugangsdaten:

leuphana.zoom.us/j/92701177112

Meeting-ID: 92701177112
Passwort: ReCoISDS