Toryn Schafer

Toryn Schafer is an Assistant Professor in the Department of Statistics at Texas A&M University, holding the 2024 ConocoPhillips Data Science Faculty Fellowship. Previously, he was a postdoctoral associate at Cornell University's Department of Statistics and Data Science, contributing to the NSF-funded PRISM Institute for Trans-domain Systemic Risk. His academic journey includes a PhD in Statistics (2020) from the University of Missouri, an MA in Statistics (2018), and a BSc in Statistics & Wildlife Biology (2014) from Colorado State University.

His research interests focus on spatio-temporal statistics, reinforcement learning, Bayesian methods, and machine learning, applied to ecological and environmental systems. He emphasizes interdisciplinary approaches to address challenges in energy, sports analytics, and biodiversity conservation.

His recent work explores advanced statistical methods for trend analysis, changepoint detection in time series, and the integration of community science data for ecological modeling. Notable contributions include Bayesian inverse reinforcement learning frameworks for animal behavior analysis and studies on renewable energy impacts on electricity markets.

• Education:
• PhD in Statistics, University of Missouri (2020)
• MA in Statistics, University of Missouri (2018)
• BSc in Statistics & Wildlife Biology, Colorado State University (2014)

Research Themes: His publications reflect a trajectory toward methodological advancements in spatio-temporal modeling, with applications ranging from animal movement patterns to energy grid resilience. Recent articles highlight critical risk indicators for power systems and biodiversity status metrics inspired by financial portfolio theory.

Grants & Fellowships: 2024 ConocoPhillips Data Science Faculty Fellowship (Texas A&M University).

Labs/Teams: While specific lab affiliations are not detailed, his work intersects with interdisciplinary teams focused on ecological data science and systemic risk analysis.