Tyler Hoffman

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(he/him) · Ph.D Student at Arizona State University in Geography

Twitter Github tdhoffman@asu.edu

Research

CV

Research Notes

Google Scholar

ORCiD

GSoC 2022 Progress Journal

Kedron Lab @ ASU

SPARC @ ASU

GEOSMASH @ UMD

About

Coming from a background of math and computer science, I develop algorithms and statistical methods for spatial data science. My work aims to better represent and mathematically model spatial problems and to chip away at our understanding of core geographical concepts, such as process and scale. Through algorithm design, I also seek to advance the principled use of (spatial) data science in social science. For more information about my research, click here (slightly outdated). In my spare time, I love watching movies, playing piano, and biking. I am a recipient of the NSF Graduate Research Fellowship and I’m currently a Ph.D student at Arizona State University in the Spatial Analysis Research Center (SPARC).

News and Updates

21 Oct 2022: I was featured on the NumFOCUS Google Summer of Code wrap-up blog post!

11 Oct 2022: I received my Master’s in Passing! I’ll be graduating with my M.A. in Geography this fall from ASU. One more step checked off on the way to a Ph.D!

28 Feb 2022: I presented at UCSB’s Spatial Lightning Talks 2022 about Private Wojtek, a bear who fought in World War 2. The video can be found here.

19 Nov 2021: I was featured during ASU Geo Week 2021!

Publications

  1. T. D. Hoffman, P. Kedron. (2022). "AM-32: Spatial autoregressive models." Geographic Information Science and Technology Body of Knowledge. In press.
  2. T. D. Hoffman, P. Kedron. (2022). "Operationalizing Spatial Causal Inference." UCSB Spatial Data Science Symposium 2022 Short Paper Proceedings. PDF. Link. Recorded presentation.
  3. P. Kedron, S. Bardin, T. D. Hoffman, M. Sachdeva, M. Quick, J. Holler. (2022). "A Replication of DiMaggio et al. (2020) in Phoenix, AZ." Annals of Epidemiology, 74, 8-14. PDF. Link.
  4. W. F. Fagan, C. Saborio, T. D. Hoffman, E. Gurarie, R. S. Cantrell, C. Cosner. (2022). "What's in a resource gradient? Comparing alternative cues for foraging in dynamic environments via movement, perception, and memory." Theoretical Ecology, open access, 1-16. PDF. Link.
  5. T. D. Hoffman, T. Oshan. (2021). "A Supervised Heuristic for a Balanced Approach to Regionalization." GIS Research UK Conference. PDF. Link.
  6. T. Hoffman*, A. Swain*, K. Leyba, W. F. Fagan. (2021). "Trade-offs in sensory characteristics shape the evolution of perception." Frontiers in Ecology and Evolution, 9. PDF. Link.
  7. A. Lawson, T. Hoffman, Y. Chung, K. Keegan, S. Day. (2021). "A density-based approach to feature detection in persistence diagrams for firn data." Foundations of Data Science. PDF. Link.
  8. W. F. Fagan, T. Hoffman, D. Dahiya, E. Gurarie, R. S. Cantrell, C. Cosner. (2019). "Improved foraging by switching between diffusion and advection: benefits from movement that depends on spatial context." Theoretical Ecology, 13 (2), 127-136. PDF. Link.

*equal contributions

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