Jessilyn Dunn

Assistant Professor in the Department 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 and 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
• Email Address: jessilyn.dunn@duke.edu
• Websites:
  • Dunn Lab

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 790: Advanced Topics for Graduate Students 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 395T: Bass Connections Information, Society & Culture Research Team
• ISS 795T: Bass Connections Information, Society & Culture Research Team

In the News

• How You Can Help Scientists Better Understand COVID Variants With Wearable Devices (Jan 27, 2022 | Duke MEDx)
• Duke Celebrates Women and Girls in Science Day (Feb 10, 2021)
• Early Detection of COVID-19: How Your Smartwatch Could Help (Aug 25, 2020 | Duke Magnify)
• School of Medicine Forum Addresses the Role of Data Science During Times of Crisis (Jul 22, 2020 | School of Medicine)
• A COVID-19 Study for Early Detection Expands to Reach New Communities (Jun 15, 2020 | Pratt School of Engineering)
• Here'e How to Make Smartwatch Health Data Useful for Research (May 15, 2020)
• Using Smartphones in the Effort for Early Detection of COVID-19 (Apr 8, 2020 | Pratt School of Engineering)
• NC Survey Tracks How Residents Are Changing Behavior In Pandemic (Apr 6, 2020)
• Your Skin Tone Won't Affect Your Heart-Tracking Device. Your Activity Might (Feb 11, 2020 | Pratt School of Engineering)
• Jessilyn Dunn: Gaining Insights from Biomedical Big Data (Jun 5, 2018 | Duke University Pratt School of Engineering)

Representative Publications

• Cho, PJ; Yi, J; Ho, E; Shandhi, MMH; Dinh, Y; Patil, A; Martin, L; Singh, G; Bent, B; Ginsburg, G; Smuck, M; Woods, C; Shaw, R; Dunn, J, Demographic Imbalances Resulting From the Bring-Your-Own-Device Study Design., Jmir Mhealth and Uhealth, vol 10 no. 4 (2022) [10.2196/29510] [abs].
• Dunn, J; Shandhi, MMH; Cho, P; Roghanizad, A; Singh, K; Wang, W; Enache, O; Stern, A; Sbahi, R; Tatar, B; Fiscus, S; Khoo, QX; Kuo, Y; Lu, X; Hsieh, J; Kalodzitsa, A; Bahmani, A; Alavi, A; Ray, U; Snyder, M; Ginsburg, G; Pasquale, D; Woods, C; Shaw, R, A Method for Intelligent Allocation of Diagnostic Testing by Leveraging Data from Commercial Wearable Devices: A Case Study on COVID-19., Res Sq (2022) [10.21203/rs.3.rs-1490524/v1] [abs].
• Shandhi, MMH; Goldsack, JC; Ryan, K; Bennion, A; Kotla, AV; Feng, A; Jiang, Y; Wang, WK; Hurst, T; Patena, J; Carini, S; Chung, J; Dunn, J, Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review., Journal of Medical Internet Research, vol 23 no. 9 (2021) [10.2196/29875] [abs].
• Bent, B; Cho, PJ; Wittmann, A; Thacker, C; Muppidi, S; Snyder, M; Crowley, MJ; Feinglos, M; Dunn, JP, Non-invasive wearables for remote monitoring of HbA1c and glucose variability: Proof of concept, Bmj Open Diabetes Research & Care, vol 9 no. 1 (2021) [10.1136/bmjdrc-2020-002027] [abs].
• Bent, B; Cho, PJ; Henriquez, M; Wittmann, A; Thacker, C; Feinglos, M; Crowley, MJ; Dunn, JP, Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches., Npj Digital Medicine, vol 4 no. 1 (2021) [10.1038/s41746-021-00465-w] [abs].