In Brief: I am a postdoc at the The McCourt School's Massive Data Institute at Georgetown University, where I am supervised by Lisa Singh and Ali Arab. We study forced migration using penalized inference and Variational Bayes.
- R package activegp: Design for and implementation of black-box sensitivity analysis using Gaussian Processes and the Active Subspace Method.
To get started, just do:
- Nathan Wycoff, Ali Arab, Katharine M. Donato, Lisa O. Singh Sparse Bayesian Lasso via a Variable-Coefficient l1 Penalty, under review <arXiv>.
- Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia, Towards On Chip Bayesian Neuromorphic Learning, <arXiv>.
- Katharine Donato, Elizabeth Jacobs, Lisa Singh, Ali Arab, and Nathan Wycoff. Using Organic Data in Migration Research
- Nathan Wycoff, Ali Arab, Katharine Donato, Lisa Singh, Elizabeth Jacobs, Kornraphop Kawintiranon, and Yaguang Liu. Forecasting Ukrainian Refugee Flows with Organic Data Sources
- RB Gramacy, A Sauer, N Wycoff Triangulation candidates for Bayesian optimization <arXiv> (To appear in Neurips 2022).
Mickaël Binois et Nathan Wycoff A survey on high-dimensional Gaussian process modeling with application to Bayesian optimization ACM Transactions on Evolutionary Learning and Optimization
-Lata Kodali, John Wenskovitch, Nathan Wycoff, Leanna House, and Chris North. Uncertainty in Interactive WMDS Visualizations, in 2019 Symposium on Visualization in Data Science. VDS’19. Vancouver, BC, Canada, 2019 <link>
-Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia, Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout, International Conference on Neuromorphic Systems 2019 <link><arXiv>
-Michelle Dowling, Nathan Wycoff, Brian Mayer, John Wenskovitch, Scotland Leman, Leanna House, Nicholas Polys, Chris North, Peter Hauck, Interactive Visual Analytics for Sensemaking with Big Text, Big Data Research <link>.
-Xin Chen, Jessica Zeitz Self, Leanna House, John E. Wenskovitch, Maoyuan Sun, Nathan Wycoff, Jane Robertson Evia, Scotland Leman, Chris North, Be the Data: Embodied Visual Analytics. IEEE Transactions on Learning Technology 11(1): 81-95 (2018). <link>
-L. Bradel, N. Wycoff, L. House and C. North, Big Text Visual Analytics in Sensemaking, 2015 Big Data Visual Analytics (BDVA), Hobart, TAS, 2015, pp. 1-8. <link>
Postdoc at Georgetown's Massive Data Institute in the McCourt School of Public Policy (Summer 2021-Present).
Givens Scholar at Argonne National Laboratory / Math and Computer Science Division (Summer 2018).
Web Dev Intern at General Dynamics Mission Systems (Summer 2016).
Business Intelligence Intern at Comprehensive Health Services (Summer 2015).
Intern for Congressman Don Young (Spring 2013).
Teaching Experience (at Virginia Tech):
Statistics for Social Scientists (Spring 2020), Instructor of Record
Probability and Statistics for Electrical Engineers (Summer 2019), Instructor of Record
Statistics for Biologists (Fall 2018), Lab Instructor
Various Grading Appointments
I founded an undergrad academic club
Virginia Tech Statistics (B.S. 2016, M.S. 2018, Ph.D 2021)