David Carlson

Assistant Professor of Civil and Environmental Engineering

Appointments and Affiliations

  • Assistant Professor of Civil and Environmental Engineering
  • Assistant Professor in Biostatistics & Bioinformatics
  • Assistant Professor of Computer Science
  • Faculty Network Member of the Duke Institute for Brain Sciences
  • Member of the Duke Clinical Research Institute

Contact Information

  • Office Location: Hudson Hall, Durham, NC 27705
  • Office Phone: (919) 668-9680
  • Email Address: david.carlson@duke.edu

Education

  • Ph.D. Duke University, 2015

Research Interests

Machine learning, predictive modeling, health data science, statistical neuroscience

Courses Taught

  • CEE 690: Advanced Topics in Civil and Environmental Engineering
  • CEE 692: Independent Study: Advanced Topics in Civil and Environmental Engineering
  • CEE 780: Internship
  • COMPSCI 393: Research Independent Study
  • COMPSCI 394: Research Independent Study
  • ECE 494: Projects in Electrical and Computer Engineering
  • EGR 190: Special Topics in Engineering
  • EGR 590: Special Topics in Engineering

In the News

Representative Publications

  • Jiang, Ziyang, Tongshu Zheng, Mike Bergin, and David Carlson. “Improving spatial variation of ground-level PM2.5 prediction with contrastive learning from satellite imagery.” Science of Remote Sensing 5 (June 2022): 100052–100052. https://doi.org/10.1016/j.srs.2022.100052.
  • Mague, Stephen D., Austin Talbot, Cameron Blount, Kathryn K. Walder-Christensen, Lara J. Duffney, Elise Adamson, Alexandra L. Bey, et al. “Brain-wide electrical dynamics encode individual appetitive social behavior.” Neuron 110, no. 10 (May 18, 2022): 1728-1741.e7. https://doi.org/10.1016/j.neuron.2022.02.016.
  • Bey, Alexandra L., Kathryn K. Walder-Christensen, Jack Goffinet, Elise Adamson, Noah Lanier, Stephen D. Mague, David Carlson, and Kafui Dzirasa. “6.28 Identifying Networks Underlying Sleep Disruption in Autism Spectrum Disorder Mouse Models.” In Journal of the American Academy of Child &Amp; Adolescent Psychiatry, 60:S167–S167. Elsevier BV, 2021. https://doi.org/10.1016/j.jaac.2021.09.101.
  • Dunn, Timothy W., Jesse D. Marshall, Kyle S. Severson, Diego E. Aldarondo, David G. C. Hildebrand, Selmaan N. Chettih, William L. Wang, et al. “Geometric deep learning enables 3D kinematic profiling across species and environments.” Nat Methods 18, no. 5 (May 2021): 564–73. https://doi.org/10.1038/s41592-021-01106-6.
  • Zheng, T., M. Bergin, G. Wang, and D. Carlson. “Local PM2.5 hotspot detector at 300 m resolution: A random forest-convolutional neural network joint model jointly trained on satellite images and meteorology.” Remote Sensing 13, no. 7 (April 1, 2021). https://doi.org/10.3390/rs13071356.