Bio


Pardis Miri, PhD, recently received her doctorate in computer science, in the area of human computer interaction, from University of California Santa Cruz. As a PhD student, she spent the last 3 years of her training at Stanford University under the supervision of Dr. Marzullo, Dr. Gross, and Dr. Isbister. For her dissertation, she took a multidisciplinary approach in using technology for affect regulation. More specifically, she explored the placement and pattern, and personalization of a vibrotactile breathing pacer system that she developed during her graduate studies. Her work was funded by the National Science Foundation and Intel labs. Prior to being a Ph.D. student, Miri earned her Master’s degree in computer science from the University of California San Diego in the area of Systems and Networking. She is currently a postdoctoral fellow at Stanford University conducting research in using vibrotactile technology to aid affect regulation in neurotypical and neurodiverse populations.

Honors & Awards


  • EAGER National Science Foundation Grant., Systems for Assisting in Emotion Regulation in the Wild. (2016-2020)
  • Facilitating Affect Regulation in Youth with Autism Spectrum Disorder, Stanford eWear Seed Grant (2020-2021)

Professional Education


  • Doctor of Philosophy, University of California Santa Cruz (2019)
  • PhD, University of California, Santa Cruz, Computer Science, HCI (2019)
  • MS, University of California, San Diego, Computer Science, Systems and Networking (2013)
  • BS, Amirkabir University of Technology, Tehran, Iran, Computer Engineering

Stanford Advisors


Patents


  • Pardis Miri; Robert Flory; Keith Marzullo; James Gross. "United States Patent S19-525 62/972,610 (S31-06632.PRO) Personalizable, Inconspicuous Vibrotactile Breathing Pacer", Stanford University, Feb 10, 2020
  • Pardis Miri; Pankaj Garg; Benjamin Schultz;Sandeep Kishan Singhal; Madhan Sivakumar. "United States Patent 8806005 Cross-machine event log correlation", Microsoft Inc, Oct 8, 0179

Projects


  • Design, Engineer, and Evaluate Technologies to Facilitate Affect Regulation, Stanford University (2016 - 2022)

    Our aim through this project is to develop and evaluate new and innovative vibrotactile technologies that assist individuals with affect regulation. A unique aspect of our contribution comes from the interdisciplinarity of our team. Included on our team are experts in emotion regulation, haptics, electrical engineering, HCI, and distributed systems, as well as experts in the clinical application of biofeedback. We believe that such an interdisciplinary approach is necessary for making progress in the development of technology that assists in affect regulation. To learn more about the specific projects please visit our page: wehab.stanford.edu

    Location

    Stanford

    Collaborators

    • Keith Marzullo, Dean and Professor, University of Maryland
    • James Gross, Professor, Stanford University
    • Antonio Hardan, Professor, Stanford University
    • Lawrence Fung, Assistant Professor, Stanford University
    • John Hegarty, School of Medicine

    For More Information:

All Publications


  • Evaluating a Personalizable, Inconspicuous Vibrotactile(PIV) Breathing Pacer for In-the-Moment Affect Regulation CHI Conference on Human Factors in Computing Systems Miri, P., Jusuf, E., Uusberg, A., Margarit, H., Flory, R., Isbister, K., Marzullo, K., Gross, J. J. 2020: 13

    View details for DOI 10.1145/3313831.3376757

  • PIV: Placement, Pattern, and Personalization of an Inconspicuous Vibrotactile Breathing Pacer ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION Miri, P., Flory, R., Uusberg, A., Culbertson, H., Harvey, R. H., Kelman, A., Peper, D., Gross, J. J., Isbister, K., Marzullo, K. 2020; 27 (1)

    View details for DOI 10.1145/3365107

    View details for Web of Science ID 000535715400005

  • Using the Neuroscience of Fear Extinction for Anxiety Reduction: Study Design, Aims, and Preliminary Data Ball, T., Miri, P., Williams, L. NATURE PUBLISHING GROUP. 2019: 267–68
  • PortLand: A Scalable Fault-Tolerant Layer 2 Data Center Network Fabric Mysore, R., Pamboris, A., Farrington, N., Huang, N., Miri, P., Radhakrishnan, S., Subramanya, V., Vandat, A., ACM ASSOC COMPUTING MACHINERY. 2009: 39–50