Jessilyn Dunn

Dunn

Assistant Professor of Biomedical Engineering

Developing new tools and infrastructure for multi-modal biomedical data integration to drive precision/personalized methods for early detection, intervention, and prevention of disease.

Appointments and Affiliations

  • Assistant Professor of Biomedical Engineering
  • Assistant Professor of Biostatistics & Bioinformatics
  • Assistant Professor in the Department of Electrical and Computer Engineering
  • Member in the Duke Clinical Research Institute

Contact Information

  • Office Location: 534 Research Dr, Room #448, Durham, NC 27708
  • Websites:

Education

  • Ph.D. Georgia Institute of Technology, 2015

Research Interests

Use of large-scale biomedical datasets to model and guide personalized therapies.

Courses Taught

  • BIOSTAT 707: Statistical Methods for Learning and Discovery
  • BME 290: Intermediate Topics (GE)
  • BME 493: Projects in Biomedical Engineering (GE)
  • BME 494: Projects in Biomedical Engineering (GE)
  • BME 580: An Introduction to Biomedical Data Science (GE)
  • BME 590: Special Topics in Biomedical Engineering
  • BME 791: Graduate Independent Study
  • BME 792: Continuation of Graduate Independent Study
  • BME 899: Special Readings in Biomedical Engineering
  • EGR 393: Research Projects in Engineering
  • HLTHPOL 395: Bass Connections COVID-19 Research Team
  • HLTHPOL 395T: Health Policy & Innovation Research Team
  • HLTHPOL 396T: Bass Connections Health Policy & Innovation Research Team
  • HLTHPOL 795: Bass Connections COVID-19 Research Team
  • HLTHPOL 795T: Bass Connections Health Policy & Innovation Research Team
  • HLTHPOL 796T: Bass Connections Health Policy & Innovation Research Team
  • ISS 290S: Special Topics in Information Science + Studies
  • ISS 395T: Bass Connections Information, Society & Culture Research Team
  • ISS 396T: Bass Connections Information, Society & Culture Research Team
  • ISS 795T: Bass Connections Information, Society & Culture Research Team
  • ISS 796T: Bass Connections Information, Society & Culture Research Team

In the News

Representative Publications

  • Chikwetu, L; Miao, Y; Woldetensae, MK; Bell, D; Goldenholz, DM; Dunn, J, Does deidentification of data from wearable devices give us a false sense of security? A systematic review., The Lancet Digital Health, vol 5 no. 4 (2023), pp. e239-e247 [10.1016/s2589-7500(22)00234-5] [abs].
  • Popham, S; Burq, M; Rainaldi, EE; Shin, S; Dunn, J; Kapur, R, An Algorithm to Classify Real-World Ambulatory Status From a Wearable Device Using Multimodal and Demographically Diverse Data: Validation Study, Jmir Biomedical Engineering, vol 8 (2023), pp. e43726-e43726 [10.2196/43726] [abs].
  • Hughes, A; Shandhi, MMH; Master, H; Dunn, J; Brittain, E, Wearable Devices in Cardiovascular Medicine., Circulation Research, vol 132 no. 5 (2023), pp. 652-670 [10.1161/circresaha.122.322389] [abs].
  • Holko, M; Lunt, C; Dunn, J, Session Introduction: Digital health technology data in biocomputing: Research efforts and considerations for expanding access., Pacific Symposium on Biocomputing, vol 28 (2023), pp. 1-6 [abs].
  • Lederer, L; Breton, A; Jeong, H; Master, H; Roghanizad, AR; Dunn, J, Considerations while using Fitbit Data in the All of Us Research Program: Tutorial (Preprint) (2022) [10.2196/preprints.45103] [abs].