Yoh Family Associate Professor of Civil and Environmental Engineering
My general research focus is on developing novel machine learning and artificial intelligence techniques that can be used to accelerate scientific discovery. I work extensively both on the fundamental theory and algorithms as well as translating them into scientific applications. I have extensive partnerships deploying machine learning techniques in environmental health, mental health, and neuroscience.
Appointments and Affiliations
- Yoh Family Associate Professor of Civil and Environmental Engineering
- Associate Professor of Civil and Environmental Engineering
- Associate Professor in Biostatistics & Bioinformatics
- Associate Professor of Biomedical Engineering
- Associate Professor of Computer Science
- Associate Professor in the Department of Electrical and Computer Engineering
- Faculty Network Member of the Duke Institute for Brain Sciences
Contact Information
- Office Location: Hudson Hall, Durham, NC 27705
- 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
- ME 555: Advanced Topics in Mechanical Engineering
- EGR 393: Research Projects in Engineering
- ECE 899: Special Readings in Electrical Engineering
- ECE 493: Projects in Electrical and Computer Engineering
- ECE 392: Projects in Electrical and Computer Engineering
- CEE 780: Internship
- CEE 690: Advanced Topics in Civil and Environmental Engineering
- CEE 491: Independent Study in Civil and Environmental Engineering
- CBB 700: Internship
- CBB 591: Independent Study
In the News
- Ten Faculty Named 2025 Bass Chairs (Apr 22, 2025 | Duke Today)
- For Many Urban Residents, It’s Hotter Than Their Weather App Says (Jun 27, 2024…
- Eyes in the Sky Bring Good News on Trash Burning in the Maldives (Jul 14, 2023 …
- Students Find Interdisciplinary Exploration and Connection in Winter Breakaway …
- David Carlson: Engineering and Machine Learning for Better Medicine (Jan 9, 201…
Representative Publications
- Zhang, H., Z. Jiang, S. Zhang, L. Tu, and D. Carlson. “Scale-free and unbiased transformer with tokenization for cell type annotation from single-cell RNA-seq data.” Pattern Recognition 168 (December 1, 2025). https://doi.org/10.1016/j.patcog.2025.111724.
- Hickman, S. H. M., M. M. Kelp, P. T. Griffiths, K. Doerksen, K. Miyazaki, E. A. Pennington, G. Koren, et al. “Applications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research.” Geoscientific Model Development 18, no. 22 (November 20, 2025): 8777–8800. https://doi.org/10.5194/gmd-18-8777-2025.
- Walder-Christensen, Kathryn K., Jack Goffinet, Alexandra L. Bey, Reah Syed, Jacob Benton, Stephen D. Mague, Elise Adamson, et al. “Sleep-Wake States Are Encoded across Emotion Regulation Regions of the Mouse Brain.” ENeuro 12, no. 11 (November 2025). https://doi.org/10.1523/ENEURO.0291-25.2025.
- Li, Keyu, Charles Wood, Liz Nichols, Zachary D. Calhoun, Nrupen A. Bhavsar, and David Carlson. “Neighborhood Environmental and Contextual Factors Improve Prediction of Childhood Body Mass Index: An Application of Novel Graph Neural Networks.” AJE Adv, September 24, 2025. https://doi.org/10.1093/ajeadv/uuaf011.
- Liu, Y., W. Shi, C. Fu, Z. Jiang, Z. Hua, and D. Carlson. “MOTTO: A Mixture-of-Experts Framework for Multi-Treatment, Multi-Outcome Treatment Effect Estimation.” In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2:1891–1902, 2025. https://doi.org/10.1145/3711896.3737056.