Jon Froehlich
Assistant Professor, Computer Science
Affiliate Assistant Professor, iSchool
University of Maryland, College Park

Contact
twitter: @jonfroehlich
email: jonf@umd.edu

CS Office:
3173 AV Williams
Department of Computer Science
University of Maryland
College Park, MD 20742

HCIL Office:
2117F Hornbake Library, South
Human-Computer Interaction Lab
University of Maryland
College Park, MD 20742

Travel/Events
My PhD Students
Kotaro Hara
Matt Mauriello

My MS Students
Michael Gubbels
Leyla Norooz
About Me
I am an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park with an affiliate appointment in the College of Information Studies. I am also a member of the Human-Computer Interaction Laboratory (HCIL), the Institute for Advanced Computer Studies (UMIACS), and the founder of the new HCIL Hackerspace and HCIL lablet: the Makeability Lab. Research in the Makeability Lab is funded, in part, by a Google Faculty Research Award, a 3M Faculty Award, and by Nokia and the NSF.

I received my Phd in Computer Science from the University of Washington in December 2011 where I was a Microsoft Research Graduate Fellow and the 2010 College of Engineering "Graduate Innovator of the Year." My PhD dissertation entitled "Sensing and Feedback of Everyday Activities to Promote Environmental Behaviors" won numerous awards including the 2012 University of Washington Distinguished Dissertation Award and an honorable mention for the national 2012 Council of Graduate Schools Distinguished Dissertation Award in Mathematics, Physical Sciences, and Engineering. At UW, I was co-advised by James Landay and Shwetak Patel. I also have an MS in Information and Computer Science from the University of California, Irvine where I was advised by Paul Dourish. During my graduate studies, I was fortunate to intern at a number of great research labs including Telefonica Research in Barcelona, Microsoft Research in Redmond, and Intel Research in Seattle.

My work has been published in over 30 scientific peer-reviewed publications in many top venues including ACM CHI, UbiComp, IJCAI, MobiSys, ASSETS, and ICSE garnering three best paper awards (CHI'10, CHI'13, ASSETS'13) and three best paper nominations (UbiComp'09, CHI'12, CHI'13). Please see my publication page and/or Google Scholar page for more details.

Research Focus
My research focuses on designing, building, and evaluating interactive technology that addresses high value social issues such as environmental sustainability, computer accessibility, and personalized health and wellness. This work often involves the entire spectrum of information flow: from sensing physical events, to intelligently interpreting/classifying this data, to building visualizations that inform and motivate behavior. Please see my list of publications here.

My research interests can broadly be broken down into four areas:

Sensing and Feedback Systems for Environmental Behaviors
There is often a profound disconnect between our everyday behaviors and the effects those behaviors have on our health and the environment around us. In this research, I explore how technology can be used to effectively sense and report information about environmental behaviors to promote awareness and enable positive behavior change. Research questions involved here include: What behaviors should we sense and how? How, where, and when should this sensed activity data be presented? And, finally, What impact can sensing and feedback have on behavior?

Smart Cities and Sustainable Transport
City-wide urban infrastructures are increasingly reliant on network technology to improve and expand their services. As a consequence, our interactions in the physical world are increasingly leaving behind digital footprints. In this research, I explore how these digital footprints can reveal otherwise latent patterns of human behavior as well as implications for the improvement of city infrastructures themselves (e.g., shared bicycling programs, rail and bus systems).

Health and Wellness
As sensors continue to decrease in size/price and advances in machine learning enable better and more granular activity recognition, there is an enormous opportunity for sensing and feedback applications for personal health particularly around sleeping, diet, and exercise. In the long term, I hope to continue building and studying applications that motivate positive behaviors for both health and the environment. Significant questions remain: What are the most effective strategies for motivating behaviors? Can systems adapt their strategies to fit the individual user? How can we use technology to sustain behaviors over time? What is the role of augmented reality and other forms of emerging media?

Computer and World Accessibility
As we increasingly rely on computers and mobile devices to support everyday tasks such as bill paying, internet browsing, and social communication, both new opportunities and new challenges emerge for those with physical and/or cognitive disabilities. My interest in computer accessibility goes beyond simply investigating how computers can be universally usable (e.g., touchscreen accessibility) but also in how computers can be used to make the world more accessible as well (e.g., studying sidewalk accessibility).

Research Approach
Although my methods extend largely from Ubiquitous Computing and Human-Computer Interaction, my research is additionally informed by perspectives in design, information visualization, economics, and behavioral and environmental psychology. I also apply knowledge from data-intensive areas such as machine learning and signal processing to help build and evaluate my sensing systems. My research process is iterative, often beginning with lightweight formative studies and, crucially, concluding with field deployments of working technology. In this way, I am interested not only in building new technologies but in studying their actual effectiveness in the field. Finally, as my work is often interdisciplinary, I frequently collaborate with researchers both within various sub-disciplines of computer science (e.g., machine learning) as well as outside of computer science (e.g., electrical engineering and psychology).
Prospective Students
I am looking for undergraduate and graduate students passionate about investigating the role of technology in solving high-value social problems. If this interests you, please contact me so that we can setup a time to chat about mutual interests and potential research projects. Also, read this.

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