Embedded Files
In Brief: I am an Assistant Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. I am interested in the nexus of statistics and optimization, including Bayesian Optimization, numerical optimization for machine learning, and variational Bayes.
Currently, I have two sponsored research projects:
How can we do sequential design of experiments in infinite dimensional spaces, such as function spaces? This is motivated by exciting work in designing wearable devices to enhance human mobility by my awesome collaborators at Umass.
How can we do transfer learning with extremely limited and questionably relevant source datasets? This is motivated by important work in predicting the course of emerging humanitarian crises with my great collaborators Georgetown.
I'm very grateful to the Air Force Office of Scientific Research, the National Science Foundation, and the National Geospatial-Intelligence Agency for supporting our work.
email: nwycoff@umass.edu
Software:
Software:
- 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:
R> install.packages("activegp")
R>example(activegp)
Selected Research Documents:
Selected Research Documents:
(For a full list, see my Google Scholar)
- Nathan Wycoff, Ali Arab, Lisa O. Singh (2025+). Formal Bayesian Transfer Learning via the Total Risk Prior, under preparation, <arXiv>.
- Nathan Wycoff (2025). Regression Trees Know Calculus, Neurips '25, <arXiv>.
- Nathan Wycoff (2024). Surrogate Active Subspaces for Jump-Discontinuous Functions, AISTATS '24 <PMLR> <arXiv> <GitHub>.
- Nathan Wycoff, Lisa O. Singh, Ali Arab, Katharine M. Donato, Helge Marahrens (2024). The digital trail of Ukraine’s 2022 refugee exodus, Journal of Computational Social Science, <JCSO> <GitHub>.
- Nathan Wycoff, Mickaël Binois & Stefan M. Wild (2021). Sequential Learning of Active Subspaces, Journal of Computational and Graphical Statistics, <arXiv>, <JCGS>.
Previous Work Experience:
Postdoc at Georgetown's Massive Data Institute in the McCourt School of Public Policy (Summer 2021-Summer 2024).
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 the late 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
Education:
Virginia Tech Statistics (B.S. 2016, M.S. 2018, Ph.D 2021)
Google Sites
Report abuse