Lawrence Carin

Lawrence Carin

Professor of Statistical Science

External address: 
119 Allen Building, Durham, NC 27708
Internal office address: 
Box 90291, Durham, NC 27708-0291
Phone: 
(919) 681-6436

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.

Education & Training

  • Ph.D., University of Maryland, College Park 1989

  • M.Sc.Eng., University of Maryland, College Park 1986

  • B.S.E., University of Maryland, College Park 1985

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

Multi-Source Activity Graph Latent Uncovering & Merging (MAGNUM) awarded by Lockheed Martin Corporation (Principal Investigator). 2017 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

Pages

Carlson, D, and Carin, L. "Continuing progress of spike sorting in the era of big data." Current Opinion in Neurobiology 55 (March 8, 2019): 90-96. (Review) Full Text

Chen, C, Wang, W, Zhang, Y, Su, Q, and Carin, L. "A convergence analysis for a class of practical variance-reduction stochastic gradient MCMC." Science China Information Sciences 62.1 (January 1, 2019). Full Text

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.

Wang, G, Li, C, Wang, W, Zhang, Y, Shen, D, Zhang, X, Henao, R, and Carin, L. "Joint embedding of words and labels for text classification." Acl 2018 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers) 1 (January 1, 2018): 2321-2331.

Shen, D, Su, Q, Chapfuwa, P, Wang, W, Wang, G, Carin, L, and Henao, R. "NasH: Toward end-to-end neural architecture for generative semantic hashing." Acl 2018 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers) 1 (January 1, 2018): 2041-2050. Open Access Copy

Shen, D, Wang, G, Wang, W, Min, MR, Su, Q, Zhang, Y, Li, C, Henao, R, and Carin, L. "Baseline needs more love: On simple word-embedding-based models and associated pooling mechanisms." Acl 2018 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers) 1 (January 1, 2018): 440-450.

Pages

Zhang, X, Yuan, X, and Carin, L. "Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration." December 14, 2018. Full Text

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.

Pages