Assistant Professor of Statistical Science
Appointments and Affiliations
- Assistant Professor of Statistical Science
- Assistant Professor in the Department of Electrical and Computer Engineering
- Assistant Professor in Neurobiology
- Assistant Professor in Neurology
- Assistant Professor of Computer Science
- Member of the Center for Cognitive Neuroscience
- Affiliate of the Duke Initiative for Science & Society
- Email Address: email@example.com
- Massachusetts Institute of Technology, 2011
- University of Cambridge (UK), 2011
- Ph.D. University College London (United Kingdom), 2008
- M.S. Columbia University, 2003
- B.S. State University of New York at Stony Brook, 2000
- BRAINSOC 395-1: Bass Connections in Brain and Society: Interdisciplinary Team Projects
- BRAINSOC 395: Bass Connections in Brain and Society: Interdisciplinary Team Projects
- BRAINSOC 396-1: Bass Connections in Brain and Society 2: Interdisciplinary Team Projects
- BRAINSOC 396: Bass Connections in Brain and Society 2: Interdisciplinary Team Projects
- COMPSCI 391: Independent Study
- ECE 891: Internship
- NEUROSCI 493: Research Independent Study 1
- STA 102: Introductory Biostatistics
- STA 571: Advanced Probabilistic Machine Learning
- STA 582L: DataFest
- STA 993: Independent Study
In the News
- iPhone App Could Guide MS Research, Treatment (Oct 3, 2017)
- New Collaborative Seed Grant Program Gives Eight Awards (Mar 16, 2016)
- UNC, Duke researchers team up to study how the flu spreads (Sep 8, 2015 | WRAL)
- How to predict which college students will get the flu (Aug 19, 2015 | Futurity)
- Cell Phones Help Track Flu on Campus (Aug 18, 2015)
- Two Duke Teams Attempting to Map LinkedIn Universe (Jun 1, 2015 | Duke Research Blog)
- Three Win NSF Awards for Brain Science (Aug 14, 2014)
- Wiens, J; Saria, S; Sendak, M; Ghassemi, M; Liu, VX; Doshi-Velez, F; Jung, K; Heller, K; Kale, D; Saeed, M; Ossorio, PN; Thadaney-Israni, S; Goldenberg, A, Author Correction: Do no harm: a roadmap for responsible machine learning for health care., Nature Medicine, vol 25 no. 10 (2019) [10.1038/s41591-019-0609-x] [abs].
- Wang, S; Fan, K; Luo, N; Cao, Y; Wu, F; Zhang, C; Heller, KA; You, L, Massive computational acceleration by using neural networks to emulate mechanism-based biological models., Nature Communications, vol 10 no. 1 (2019) [10.1038/s41467-019-12342-y] [abs].
- Wiens, J; Saria, S; Sendak, M; Ghassemi, M; Liu, VX; Doshi-Velez, F; Jung, K; Heller, K; Kale, D; Saeed, M; Ossorio, PN; Thadaney-Israni, S; Goldenberg, A, Do no harm: a roadmap for responsible machine learning for health care., Nature Medicine, vol 25 no. 9 (2019), pp. 1337-1340 [10.1038/s41591-019-0548-6] [abs].
- Wei, Q; Fan, K; Wang, W; Zheng, T; Amit, C; Heller, K; Chen, C; Ren, K, InverseNet: Solving inverse problems of multimedia data with splitting networks, Proceedings Ieee International Conference on Multimedia and Expo, vol 2019-July (2019), pp. 1324-1329 [10.1109/ICME.2019.00230] [abs].
- Corey, KM; Kashyap, S; Lorenzi, E; Lagoo-Deenadayalan, SA; Heller, K; Whalen, K; Balu, S; Heflin, MT; McDonald, SR; Swaminathan, M; Sendak, M, Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study., Plos Medicine, vol 15 no. 11 (2018) [10.1371/journal.pmed.1002701] [abs].