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 - Track V of Biostatistics and Bioinformatics
• Member in the Duke Clinical Research Institute

Contact Information

• Office Location: Suite 1102 Hock Plaza, Box 2721, 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

• BME 493: Projects in Biomedical Engineering (GE)
• BME 494: Projects in Biomedical Engineering (GE)
• BME 590: Special Topics in Biomedical Engineering
• BME 791: Graduate Independent Study
• BME 792: Continuation of Graduate Independent Study
• COMPSCI 393: Research Independent Study

In the News

• 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

• Jiang, Y; Qi, Y; Wang, WK; Bent, B; Avram, R; Olgin, J; Dunn, J, EventDTW: An Improved Dynamic Time Warping Algorithm for Aligning Biomedical Signals of Nonuniform Sampling Frequencies., Sensors (Basel, Switzerland), vol 20 no. 9 (2020) [10.3390/s20092700] [abs].
• Goldsack, JC; Coravos, A; Bakker, JP; Bent, B; Dowling, AV; Fitzer-Attas, C; Godfrey, A; Godino, JG; Gujar, N; Izmailova, E; Manta, C; Peterson, B; Vandendriessche, B; Wood, WA; Wang, KW; Dunn, J, Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs)., Npj Digital Medicine, vol 3 (2020) [10.1038/s41746-020-0260-4] [abs].
• Bent, B; Goldstein, BA; Kibbe, WA; Dunn, JP, Investigating sources of inaccuracy in wearable optical heart rate sensors., Npj Digital Medicine, vol 3 (2020) [10.1038/s41746-020-0226-6] [abs].
• Witt, DR; Kellogg, RA; Snyder, MP; Dunn, J, Windows into human health through wearables data analytics, Current Opinion in Biomedical Engineering, vol 9 (2019), pp. 28-46 [10.1016/j.cobme.2019.01.001] [abs].
• Rego, S; Dagan-Rosenfeld, O; Zhou, W; Sailani, MR; Limcaoco, P; Colbert, E; Avina, M; Wheeler, J; Craig, C; Salins, D; Röst, HL; Dunn, J; McLaughlin, T; Steinmetz, LM; Bernstein, JA; Snyder, MP, High-frequency actionable pathogenic exome variants in an average-risk cohort, Molecular Case Studies, vol 4 no. 6 (2018), pp. a003178-a003178 [10.1101/mcs.a003178] [abs].