David Carlson


Assistant Professor of Civil and Environmental Engineering

Appointments and Affiliations

  • Assistant Professor of Civil and Environmental Engineering
  • Assistant Professor in Biostatistics and Bioinformatics
  • Assistant Professor in the Department of Electrical and Computer Engineering
  • 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


  • 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
  • ECE 494: Projects in Electrical and Computer Engineering
  • ECE 590: Advanced Topics in Electrical and Computer Engineering
  • ECE 899: Special Readings in Electrical Engineering
  • EGR 190: Special Topics in Engineering
  • EGR 590: Special Topics in Engineering
  • POE 190: Practice Oriented Education
  • POE 790: Practice Oriented Education

In the News

Representative Publications

  • Loring, Z; Mehrotra, S; Piccini, JP; Camm, J; Carlson, D; Fonarow, GC; Fox, KAA; Peterson, ED; Pieper, K; Kakkar, AK, Machine learning does not improve upon traditional regression in predicting outcomes in atrial fibrillation: an analysis of the ORBIT-AF and GARFIELD-AF registries., Europace (2020) [10.1093/europace/euaa172] [abs].
  • Isaev, DY; Tchapyjnikov, D; Cotten, CM; Tanaka, D; Martinez, N; Bertran, M; Sapiro, G; Carlson, D, Attention-Based Network for Weak Labels in Neonatal Seizure Detection., Proceedings of Machine Learning Research, vol 126 (2020), pp. 479-507 [abs].
  • Zheng, T; Bergin, MH; Hu, S; Miller, J; Carlson, DE, Estimating ground-level PM2.5 using micro-satellite images by a convolutional neural network and random forest approach, Atmospheric Environment, vol 230 (2020) [10.1016/j.atmosenv.2020.117451] [abs].
  • Li, Y; Murias, M; Major, S; Dawson, G; Carlson, DE, On target shift in adversarial domain adaptation, Aistats 2019 22nd International Conference on Artificial Intelligence and Statistics (2020) [abs].
  • Cheng, P; Li, Y; Zhang, X; Cheng, L; Carlson, D; Carin, L, Gaussian-Process-Based Dynamic Embedding for Textual Networks, Aaai Conference on Artificial Intelligence (2020) [abs].