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Past Talks

Dr. Liz Bowman

Dr. Elizabeth Bowman
U.S. Army Research Laboratory
Artificial Intelligence, Machine Learning and Information: Army Social Computing Research
Tuesday, December 5th
Haldeman 041 Kreindler Conference Room
4:00 PM

Dr. Fabio Pierazzi

Dr. Fabio Pierazzi
Royal Holloway University of London
Network Security Analytics for Detection of Advanced Cyberattacks
Tuesday, November 28th
Sudikoff Trust Lab (L045)
12:30 PM

V.S. Subrahmanian

V.S. Subrahmanian
Dartmouth Distinguished Professor in Cybersecurity, Technology, and Society
Bots, Socks, and Vandals
Tuesday, November 14th
Carson L01
5:00 PM 

Rand Beers

Rand Beers ('64)
Big Data, the Internet, and Social Media:  The Road to the November 2016 Election
Wednesday, November 8th
Haldeman 41 (Kreindler Conference Hall)
4:30 PM 

Fright Night Imge

Wanna See Something REALLY Scary?
ISTS Looks at the Dark Web on Halloween Night
Tuesday, October 31st
S
udikoff  045 Trust Lab (dungeon)
7:30 PM - RSVP
Space is Limited 

Sal Stolfo

Salvatore J. Stolfo 
Columbia University
A Brief History of Symbiote Defense
Tuesday, October 31st
Rockefeller 003
5:00 PM

Dan Wallach

STAR-Vote: A Secure, Transparent, Auditable and Reliable Voting System

Professor Dan Wallach
Rice University
Thursday April 27, 2017
Carson L01, 5:00 PM

Ben Miller Dragos

Pandora's Power Grid - What Can State Attacks Do and What Would be the Impact?

Ben Miller
Chief Threat Officer, Dragos, Inc.
Tuesday May 2, 2017
Kemeny 007, 4:30 PM
Brendan Nyhan

 

 

 

Factual Echo Chambers? Fact-checking and Fake News in Election 2016.

Professor Brendan Nyhan
Dartmouth College
Thursday May 4, 2017
Rocky 001, 5:00 PM

Dickie George

 

Espionage and Intelligence

Professor Dickie George
Johns Hopkins University
Thursday May 11, 2017
Rocky 001, 5:00 PM

Dan Wallach

A Nation Under Attack: Advanced Cyber-Attacks in Ukraine

Ukrainian Cybersecurity Researchers
Thursday April 6, 2017
Oopik Auditorium 5:30 PM

ISTS Information Pamphlet


2012BrochureCover

 

Institute for Security, Technology, and Society
Dartmouth College
6211 Sudikoff Laboratory
Hanover, NH 03755 USA
info.ists@dartmouth.edu
HomeEvents >

Mobile Measurement of Behavioral and Social Health at Population Scale

Wednesday May 23, 2012
Santosh Kumar
University of Memphis
Co-Sponsored by ISTS, the CS Colloquium, and the Psychiatric Research Center's (PRC) Center for Technology and Behavioral Health (CTBH)

Abstract

Santosh Kumar
Santosh Kumar
University of Memphis

Daily behaviors such as stress, addiction, diet, exercise, and social interactions are the strongest determinant of health and mortality. Mobile phones can be used to help individuals abstain from unhealthy behaviors (e.g., addiction) and motivate them to initiate and maintain healthy behaviors (e.g., regular exercise). Such interventions, however, require reliable measurement of daily behaviors in the mobile environment. Sensors worn on the body and embedded in mobile phones collect data to enable inference of daily behaviors, but the challenge is the non-specificity of the measures such sensors collect when used in the natural environment.

In the AutoSense project, we have developed a comprehensive suite of wearable sensors that can be worn in the mobile environment to collect multiple physiological indices of stress and addictive behavior (e.g., ECG, Respiration, Alcohol, etc.). AutoSense is complemented by a software framework on the mobile phone called FieldStream that collects physiological measurements from AutoSense sensors, processes them to derive behavioral inferences, and uses these behavioral events to solicit self-reports on the phone, all in real-time. The entire end-to-end system has been worn by 50+ human volunteers for 2,500+ hours in their natural environments as part of various scientific user studies. From these real-life sensor measurements, we have developed robust models to infer psychological stress, to detect conversation episodes, and to detect smoking episodes in the field. We find that people are stressed 27% of their day and that the average duration of a conversation is 3.8 minutes, among several other interesting results on naturally occurring human behaviors. In this talk, I will introduce the AutoSense and FieldStream platforms and describe the advances we are making in automatically inferring daily behaviors such as stress, conversation, smoking, craving, and drug usage, from sensor measurements collected in the natural environment.

Bio

Santosh Kumar is an Associate Professor of Computer Science and Faudree Professor at the University of Memphis. He received his Ph.D. in Computer Science and Engineering from the Ohio State University in 2006, where his dissertation work won the SBC Presidential Fellowship award. In 2010, the Popular Science magazine named him one of America's ten most brilliant scientists under the age of 38 for leading the development of the AutoWitness burglar tracking system and the AutoSense wearable sensor system. On the theory side, he is known for establishing new models of coverage with wireless sensors such as barrier coverage for intrusion detection and trap coverage for target tracking.

His current work focuses on mobile health, where he leads the AutoSense project as part of the Genes Environment Initiative (GEI) at NIH and the FieldStream project, a large NetSE project from NSF. On these projects, he leads a multidisciplinary team of researcher from Carnegie Mellon, Georgia Tech, UCLA, UMass Amherst, Ohio State, University of Minnesota, and University of Pittsburgh. Recently, he chaired the national meeting on "mHealth Evidence" hosted at NIH and co-organized by NIH, NSF, Robert Wood Johnson Foundation, and McKesson Foundation. More information on him is available at his homepage: http://www.cs.memphis.edu/~santosh/.

Video and Slides

Santosh's slides

 

Last Updated: 6/12/12