Alexander C. Murph
Assistant Professor at the University of Pittsburgh
Guest Scientist at Los Alamos National Laboratory
Pittsburgh, PA
Assistant Professor at the University of Pittsburgh
Guest Scientist at Los Alamos National Laboratory
Pittsburgh, PA
https://orcid.org/0000-0001-7170-867X
Research Interests
My research develops statistically rigorous methods for decision-making under uncertainty across multiple scientific domains, especially in settings where classical assumptions break down: non-Euclidean parameter spaces, massive physics simulators with intrinsic stochasticity, and limited historical data. I work collaboratively with domain scientists to build practical forecasting and uncertainty quantification tools that are both methodologically principled and operationally useful, including disease-agnostic ensemble learning for infectious disease prediction, modeling and understanding Solar Energetic Particle events for national security applications, and sensitivity analysis and bias correction for multi-fidelity discrete fracture network models. Alongside these applied efforts, I maintain an ongoing interest in the theory and computation of generalized fiducial and Bayesian inference, inference on differentiable manifolds and geometric perspectives on uncertainty, and methods based on Dempster-Shafer calculus. Across all areas, my goal is to deliver deployable methods with careful attention to reproducibility and open software.
Recent News
| 01 Oct 2026 | Started work as an Assistant Professor in the Department of Psychiatry in the University of Pittsburgh. Go Panthers! |
| 31 Aug 2026 | Our disease forecasting with synthetic data and genetic information paper was published in PLOS Computational Biology |
| 15 Jan 2026 | Our disease-agnostic ensemble learning paper was accepted to Nature Communications. |
| 01 Dec 2025 | Served as Keynote Speaker at the Residential Colleges Symposium at Bucknell University. |
| 15 Nov 2025 | Presented a poster at Epidemics in San Diego, CA. |