In Press! Sensus: A Cross-Platform, General-Purpose System for Mobile Crowdsensing in Human-Subject Studies

For the past two years we have been building Sensus, a cross-platform system for crowdsensing. You can read more about Sensus here, as well as in the attached paper preview. We'll be presenting the paper at UbiComp 2016 in Heidelberg, Germany in September. Please get in touch with us at if you are interested in using Sensus in your research.

University of Virginia seeks 8 new faculty and 16 new graduate students in CPS

The University of Virginia School of Engineering and Applied Science has launched a multi-million dollar initiative to create a collaborative world class center of research excellence in Cyber-Physical Systems. This initiative includes an international search for new faculty members and graduate students across 5 different departments:

• Civil and Environmental Engineering
• Computer Science
• Electrical and Computer Engineering
• Mechanical and Aerospace Engineering
• Systems and Information Engineering

Identifying Correlates of Homicide Rates in Michoacan, Mexico

[kruger2015identifying] Kruger, C., and M. Gerber, "Identifying Correlates of Homicide Rates in Michoacan, Mexico", Social Computing, Behavioral-Cultural Modeling, and Prediction: Springer, 2015.

Forecasting Violent Extremist Cyber-Recruitment

[gerber2015forecasting] Gerber, M., and J. Scanlon, "Forecasting Violent Extremist Cyber-Recruitment", IEEE Transactions on Information Forensics and Security, vol. 10, issue 11, pp. 2461-2470, 2015.

Model Adaptation for Personalized Opinion Analysis

[alboni2015model] AlBoni, M., K. Q. Zhou, H. Wang, and M. Gerber, "Model Adaptation for Personalized Opinion Analysis", The 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, Beijing, China, Association for Computational Linguistics, 07/2015.

Seeking testers for new mobile sensing app: Sensus

The PTL is developing a new cross-platform (Android, iOS, and WinPhone) app for mobile sensing. We looked carefully at alternatives (e.g., Funf), and concluded that no existing app quite fit the bill in terms of extensibility, user interaction, and portability across platforms. So we are building our own, and we're calling it Sensus. We have finished an early version of the Android implementation and have released it to the Google Play Store.

Mobile Crowd-Sensing

Many of us spend the bulk of our time -- both awake and asleep -- in the company of smartphones, wearable fitness trackers, and countless other devices with sensing and interaction capabilities. Given their powers of observation, one might expect these devices to learn a great deal about our objectives, preferences, routines, and capabilities. One might expect them to accurately predict our behaviors and actively assist us in our daily lives. Such expectations are not being met. Our devices exhibit very few of the intelligent behaviors we might expect a human observer to acquire.

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