David Carlson is an Assistant Professor in the Department of Civil and Environmental Engineering and the Department of Biostatistics and Bioinformatics. He is also a member of the Duke Clinical Research Institute. He previously completed postdoctoral training at Columbia University and received his Ph.D in Electrical and Computer Engineering from Duke University. His research is focused in machine learning and data-driven science; in particular how machine learning and statistical techniques can be used not only for the analysis of large data sets, but integrated into the design of novel experiments to elucidate scientific understanding. He has developed algorithms and analysis methods for diverse engineering and health applications, with a special focus in neuroscience and psychiatric disorders.
Y. Li, M. Murias, S. Major, G. Dawson, K. Dzirasa, L. Carin, D. E. Carlson. Targeting EEG/LFP Synchrony with Neural Nets. Advances in Neural Information Processing Systems (NeurIPS) 2017.
Y. Li, M. Murias, S. Major, G. Dawson, D. E. Carlson. Extracting Relationships by Multi-Domain Matching. Neural Information Processing Systems (NeurIPS) 2018.
R. Hultman, K. Ulrich, B. D. Sachs, C. Blount, D. E. Carlson, N. Ndubuizu, R. C. Bagot, E. M. Parise, M.-A. T. Vu, N. M. Gallagher, J. Wang, A. J. Silva, K. Deisseroth, S. D. Mague, M. G. Caron, E. J. Nestler, L. Carin, K. Dzirasa. Brain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability. Cell 2018.
D. Carlson*, L. K. David*, N. M. Gallagher*, L. Lin*, M.-A. T. Vu, D. J. Urban, S. Srivastava, M. Shirley, R. Hultman, C. Burrus, J. Wang, C. A. McClung, S. Kumar, D. Dunson, L. Carin, S. D. Mague, K. Dzirasa. Dynamically Timed Stimulation of Corticolimbic Circuitry Activates a Stress-Compensatory Pathway. Biological Psychiatry, 2017.