Timothy Dunn

Assistant Professor of Biomedical Engineering

Appointments and Affiliations

  • Assistant Professor of Biomedical Engineering
  • Assistant Professor in Neurobiology
  • Assistant Professor in the Department of Electrical and Computer Engineering
  • Assistant Professor in Neurosurgery
  • Member of the Center for Cognitive Neuroscience

Contact Information

Education

  • Ph.D. Harvard University, 2015

Research Interests

Machine learning, computer vision, neurobiology, animal behavior, computational neuroscience, prognostic modeling, traumatic brain injury

Awards, Honors, and Distinctions

  • Technological Innovations in Neuroscience Award. McKnight Foundation. 2021
  • Peer Recognition Honor. Duke, Pratt School of Engineering. 2020
  • AI Watson XPrize Finalist (with team DataKind). IBM. 2017
  • Certificate of Distinction in Teaching. Harvard University . 2017
  • Certificate of Excellence in Teaching. Harvard University. 2017
  • Certificate of Distinction in Teaching. Harvard University . 2013
  • Graduate Research Fellowship. National Science Foundation . 2010
  • MCB Department Citation (Best in Class). UC Berkeley. 2008
  • I.L. Chaikoff Award for Undergraduate Research. UC Berkeley . 2008

Courses Taught

  • EGR 393: Research Projects in Engineering
  • ECE 899: Special Readings in Electrical Engineering
  • ECE 493: Projects in Electrical and Computer Engineering
  • BME 899: Special Readings in Biomedical Engineering
  • BME 792: Continuation of Graduate Independent Study
  • BME 791: Graduate Independent Study
  • BME 789: Internship in Biomedical Engineering
  • BME 590: Special Topics in Biomedical Engineering
  • BME 580: An Introduction to Biomedical Data Science (GE)
  • BME 494: Projects in Biomedical Engineering (GE)
  • BME 493: Projects in Biomedical Engineering (GE)
  • BME 394: Projects in Biomedical Engineering (GE)
  • AIPI 591: Special Readings in AI for Product Innovation

In the News

Representative Publications

  • Li, Tianqing, Kyle S. Severson, Fan Wang, and Timothy W. Dunn. “Improved 3D Markerless Mouse Pose Estimation Using Temporal Semi-Supervision.” Int J Comput Vis 131, no. 6 (June 2023): 1389–1405. https://doi.org/10.1007/s11263-023-01756-3.
  • Thomson, Eric E., Mark Harfouche, Kanghyun Kim, Pavan C. Konda, Catherine W. Seitz, Colin Cooke, Shiqi Xu, et al. “Gigapixel imaging with a novel multi-camera array microscope.” Elife 11 (December 14, 2022). https://doi.org/10.7554/eLife.74988.
  • Adil, Syed M., Cyrus Elahi, Dev N. Patel, Andreas Seas, Pranav I. Warman, Anthony T. Fuller, Michael M. Haglund, and Timothy W. Dunn. “Deep Learning to Predict Traumatic Brain Injury Outcomes in the Low-Resource Setting.” World Neurosurg 164 (August 2022): e8–16. https://doi.org/10.1016/j.wneu.2022.02.097.
  • Adil, Syed M., Lefko T. Charalambous, Shashank Rajkumar, Andreas Seas, Pranav I. Warman, Kelly R. Murphy, Shervin Rahimpour, et al. “Machine Learning to Predict Successful Opioid Dose Reduction or Stabilization After Spinal Cord Stimulation.” Neurosurgery 91, no. 2 (August 1, 2022): 272–79. https://doi.org/10.1227/neu.0000000000001969.
  • Kirsch, Elayna P., Alexander Suarez, Katherine E. McDaniel, Rajeev Dharmapurikar, Timothy Dunn, Shivanand P. Lad, and Michael M. Haglund. “Construct validity of the Surgical Autonomy Program for the training of neurosurgical residents.” Neurosurg Focus 53, no. 2 (August 2022): E8. https://doi.org/10.3171/2022.5.FOCUS22166.