Katherine Heller
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
Contact Information
- Email Address: katherine.heller@duke.edu
Education
- 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
Courses Taught
- 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
- STA 102: Introductory Biostatistics
- 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)
Representative Publications
- Dusenberry, MW; Tran, D; Choi, E; Kemp, J; Nixon, J; Jerfel, G; Heller, K; Dai, AM, Analyzing the role of model uncertainty for electronic health records, Acm Chil 2020 Proceedings of the 2020 Acm Conference on Health, Inference, and Learning (2020), pp. 204-213 [10.1145/3368555.3384457] [abs].
- Lorenzi, E; Henao, R; Heller, K, Hierarchical infinite factor models for improving the prediction of surgical complications for geriatric patients, The Annals of Applied Statistics, vol 13 no. 4 (2019), pp. 2637-2661 [10.1214/19-AOAS1292] [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, 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].