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 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
- ECE 494: Projects 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
- Students Find Interdisciplinary Exploration and Connection in Winter Breakaway Courses (Jan 21, 2021)
- David Carlson: Engineering and Machine Learning for Better Medicine (Jan 9, 2018 | Duke Research Blog)
- David Carlson: Generating Scientific Understanding from Machine Learning (Aug 24, 2017 | Pratt School of Engineering)
Representative Publications
- Dunn, TW; Marshall, JD; Severson, KS; Aldarondo, DE; Hildebrand, DGC; Chettih, SN; Wang, WL; Gellis, AJ; Carlson, DE; Aronov, D; Freiwald, WA; Wang, F; Ölveczky, BP, Geometric deep learning enables 3D kinematic profiling across species and environments., Nat Methods, vol 18 no. 5 (2021), pp. 564-573 [10.1038/s41592-021-01106-6] [abs].
- Zheng, T; Bergin, M; Wang, G; Carlson, D, 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, vol 13 no. 7 (2021) [10.3390/rs13071356] [abs].
- 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, vol 22 no. 11 (2020), pp. 1635-1644 [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., Proc Mach Learn Res, 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].