Bio

Ph.D., Computer Science and Information Technology University of Copenhagen 2011M.Sc., Computer Science University of Copenhagen Copenhagen, Denmark 2007B.Sc., Mathematics and Computer Science Shahid Bahonar University Kerman, Iran 1996

My research is at the intersection of health, mobile and ubiquitous computing, AI, and HCI. I work on computational modeling of human behavior (incl. Activity Recognition) from data streams collected through mobile, wearable, and embedded sensors. Examples of my work in the health domain include detection of behavior change in people with depression, predicting mania-depression episodes in bipolar disorder, estimation of symptom severity in cancer patients, and modeling of surgical activities inside the operating room.

I also work on intelligent applications for social good. My recent work in Context-aware Peer-to-Peer economic exchange is focused on connecting communities of people through mobile technology to enable successful and meaningful service transactions, especially in low-income communities. In my research, I draw on methods from Machine Learning, Data Mining, Statistics, and Human-Computer Interaction.

Research Interests

  • Human-Centered Computing
  • Ubiquitous and Mobile Computing
  • AI
  • Machine Learning
  • Data Mining
  • Health Informatics

Selected Publications

  • Identifying Symptoms Using Technology. In: Moreno M., Radovic A. (eds) Technology and Adolescent Mental Health. Springer, Cham, 2018.
  • Jakob Bardram, Afsaneh Doryab, and Sofiane Gueddana. Activity-Based Computing, Metaphors, and Technologies for Distributed User Interfaces. In Distributed User Interfaces, Human-Computer Interaction Series 2011, pp 67-74. Springer, 2011.
  • Afsaneh Doryab, Victoria Bellotti, Alaaeddine Yousfi, Shuobi Wu, John M. Carroll, and Anind K. Dey. If It’s Convenient: Leveraging Context in Peer-to-Peer Variable Service Transaction Recommendations. In the Proceedings of the ACM on Interactive, Mobile,

Featured Grants & Projects

  • Computational Modeling of Human Rhythms


    A newly funded NSF project, more details will follow soon.

  • Campus Life, Assessment of Student Health and Success


    A cross-institution collaboration with multiple universities incl. Georgia Tech, Cornell, Dartmouth, Carnegie Mellon, and the University of Washington to assess students health and performance from passive mobile data. Led two semester-long data collection studies with 450 undergraduate students at CMU.

  • Context-aware Peer to Peer Exchange


    An NSF funded project in collaboration with Penn State University and PARC to connect people in communities and help them exchange services and resources through a context-aware mobile infrastructure. NeighborGenie App for transportshare: https://itunes.apple.com/us/app/neighborgenie/id1168767544?mt=8