Lawrence Carin
Professor of Statistical Science
Overview
Lawrence Carin earned the BS, MS, and PhD degrees in electrical engineering at the University of Maryland, College Park, in 1985, 1986, and 1989, respectively. In 1989 he joined the Electrical Engineering Department at Polytechnic University (Brooklyn) as an Assistant Professor, and became an Associate Professor there in 1994. In September 1995 he joined the Electrical Engineering Department at Duke University, where he is now a Professor, and Vice Provost for Research. From 2003-2014 he held the William H. Younger Distinguished Professorship, and he was ECE Department Chair from 2011-2014. Dr Carin's early research was in the area of electromagentics and sensing, and over the last 15 years his research has moved to applied statistics and machine learning. He has recently served on the Program Committee for the following machine learning conferences: International Conf. on Machine Learning (ICML), Neural and Information Processing Systems (NIPS), Artificial Intelligence and Statistics (AISTATS), and Uncertainty in Artificial Intelligence (UAI). He was previously an Associate Editor (AE) of the IEEE Trans. on Antennas and Propagation, the IEEE Trans. on Signal Processing, and the SIAM J. of Imaging Science. He is currently an AE for the J. of Machine Learning Research. He is an IEEE Fellow.
Selected Grants
Advancing Artificial Intelligence for the Naval Domain awarded by Office of Naval Research (Principal Investigator). 2018 to 2022
Medical Scientist Training Program awarded by National Institutes of Health (Mentor). 1997 to 2022
Postdoctoral Training in Genomic Medicine Research awarded by National Institutes of Health (Mentor). 2017 to 2022
Adversarial Learning for Nonproliferation Applications awarded by Triad National Security, LLC (Principal Investigator). 2018 to 2021
RI: Small: Feature Encoding for Reinforcement Learning awarded by National Science Foundation (Co-Principal Investigator). 2018 to 2021
Bioinformatics and Computational Biology Training Program awarded by National Institutes of Health (Mentor). 2005 to 2021
Deep Learning for Sonar awarded by Office of Naval Research (Principal Investigator). 2018 to 2020
Deep learning-based image analysis for assessing real-time smoking risk awarded by National Institutes of Health (Co Investigator). 2018 to 2020
GP Kernels for Cross-Spectrum Analysis of Dynamic Networks awarded by Office of Naval Research (Principal Investigator). 2017 to 2020
QuBBD: Deep Poisson Methods for Biomedical Time-to-Event and Longitudinal Data awarded by National Institutes of Health (Co-Principal Investigator). 2017 to 2020
Pages
Carin, L, and Pencina, MJ. "On Deep Learning for Medical Image Analysis." Jama 320.11 (September 2018): 1192-1193. Full Text
Hultman, R, Ulrich, K, Sachs, BD, Blount, C, Carlson, DE, Ndubuizu, N, Bagot, RC, Parise, EM, Vu, M-AT, Gallagher, NM, Wang, J, Silva, AJ, Deisseroth, K, Mague, SD, Caron, MG, Nestler, EJ, Carin, L, and Dzirasa, K. "Brain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability." Cell 173.1 (March 2018): 166-180.e14. Full Text
Pu, Y, Dai, S, Gan, Z, Wang, W, Wang, G, Zhang, Y, Henao, R, and Carin, L. "JointGAN: Multi-domain joint distribution learning with generative adversarial nets." 35th International Conference on Machine Learning, Icml 2018 9 (January 1, 2018): 6626-6635.
Chapfuwa, P, Tao, C, Li, C, Page, C, Goldstein, B, Carin, L, and Henao, R. "Adversarial time-to-event modeling." 35th International Conference on Machine Learning, Icml 2018 2 (January 1, 2018): 1143-1156.
Shen, D, Zhang, Y, Henao, R, Su, Q, and Carin, L. "Deconvolutional latent-variable model for text sequence matching." 32nd Aaai Conference on Artificial Intelligence, Aaai 2018 (January 1, 2018): 5438-5445.
Carlson, D, David, LK, Gallagher, NM, Vu, M-AT, Shirley, M, Hultman, R, Wang, J, Burrus, C, McClung, CA, Kumar, S, Carin, L, Mague, SD, and Dzirasa, K. "Dynamically Timed Stimulation of Corticolimbic Circuitry Activates a Stress-Compensatory Pathway." Biological Psychiatry 82.12 (December 2017): 904-913. Full Text
Wang, L, Chen, M, Rodrigues, M, Wilcox, D, Calderbank, R, and Carin, L. "Information-Theoretic Compressive Measurement Design." IEEE transactions on pattern analysis and machine intelligence 39.6 (June 2017): 1150-1164. Full Text
Pu, Y, Wang, W, Henao, R, Chen, L, Gan, Z, Li, C, and Carin, L. "Adversarial symmetric variational autoencoder." Advances in Neural Information Processing Systems 2017-December (January 1, 2017): 4331-4340.
Zhang, Y, Chen, C, Gan, Z, Henao, R, and Carin, L. "Stochastic gradient monomial gamma sampler." 34th International Conference on Machine Learning, Icml 2017 8 (January 1, 2017): 6083-6092.
Zhang, Y, Gan, Z, Fan, K, Chen, Z, Henao, R, Shen, D, and Carin, L. "Adversarial feature matching for text generation." 34th International Conference on Machine Learning, Icml 2017 8 (January 1, 2017): 6093-6102.
Pages
Liang, K, Gregory, C, Diallo, SO, Roe, K, Heilmann, G, Carin, L, Carlson, D, Spell, G, and Sigman, J. "Automatic threat recognition of prohibited items at aviation checkpoint with x-ray imaging: a deep learning approach." Anomaly Detection and Imaging with X-Rays (ADIX) III. April 15, 2018 - April 19, 2018.: SPIE, April 27, 2018. Full Text
Xu, H, Luo, D, and Carin, L. "Online continuous-time tensor factorization based on pairwise interactive point processes." January 1, 2018.
Zhang, R, Chen, C, Li, C, and Carin, L. "Policy optimization as wasserstein gradient flows." January 1, 2018.
Chen, C, Li, C, Chen, L, Wang, W, Pu, Y, and Carin, L. "Continuous-time flows for efficient inference and density estimation." January 1, 2018.
Tao, C, Chen, L, Henao, R, Feng, J, and Carin, L. "X2 generative adversarial network." January 1, 2018.
Tao, C, Chen, L, Henao, R, Feng, J, and Carin, L. "Supplementary material for "x2 Generative Adversarial Net"." January 1, 2018.
Tao, C, Chen, L, Zhang, R, Henao, R, and Carin, L. "Variational inference and model selection with generalized evidence bounds." January 1, 2018.
Xu, H, Carin, L, and Zha, H. "Learning registered point processes from idiosyncratic observations." January 1, 2018.
Wei, Q, Ren, Y, Hou, R, Shi, B, Lo, JY, and Carin, L. "Anomaly detection for medical images based on a one-class classification." January 1, 2018. Full Text
Li, Y, Min, MR, Shen, D, Carlson, D, and Carin, L. "Video generation from text." January 1, 2018.