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Research
Research: Welcome
I am interested in stochastic processes and modeling in biological systems, the interplay of structure and dynamics in networks, and Bayesian inference and inverse problems. My work relies heavily on linear algebra, non-equilibrium thermodynamics, optimization, and computational topology.
I currently work on variational inference problems, noise propagation in biological networks, self-organizing edge flows, and functional form game theory (with exciting applications to multi-agent training and visualization). My published work includes the study of extinction events and large deviations, geometric solutions to moment closure problems, and the characterization of network structure in tournaments. I also work on data visualization techniques that summarize the interactions of competing agents.
I received the 2022 Suzuki Postdoctoral Fellowship Award in recognition of my research.
Research: About
Research: About
Highlights
Research: Services
Publications
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H. Kim, D. Sanz-Alonso, and A. Strang. Hierarchical Ensemble Kalman Methods with Sparsity Promoting Generalized Gamma Hyper-priors. Foundations of Data Science (2023)
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D. Chen, A. Strang, A. W. Eckford, and P. Thomas. Explicitly Solvable Continuous-time Inference for Partially Observed Markov Processes. IEEE Transactions of Signal Processing (2022)
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Z. Si, Y. Liu, and A. Strang. Path-following methods for Maximum a Posteriori estimators in Bayesian hierarchical models: How estimates depend on hyperparameters. arXiv (2022)
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A. Strang, D. SeWell, A. Kim, K. Alcedo, and D. Rosenbluth. Principal Trade-off Analysis. arXiv (2022)
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C. Cebra, and A. Strang. Similarity Suppresses Cyclicity: Why Similar Competitors Form Hierarchies. arXiv (2022)
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S. Agrawal, H. Kim, D. Sanz-Alonso, and A. Strang. A Variational Approach to Inverse Problems with Gamma Hyperpriors. SIAM Uncertainty Quantification (2022)
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A. Strang, K. C. Abbott, and P. J. Thomas. The Network HHD: Quantifying Cyclic Competition in Trait-Performance Models of Tournaments. SIREV (2022)
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A. Strang, K. C. Abbott, and P. J. Thomas. The Network HHD: Quantifying Cyclic Competition in Trait-Performance Models of Tournaments. SIREV (2021)
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Patterson, Amy, A. Strang and K. C. Abbott. When and where we can expect to see early warning signals in multispecies systems approaching tipping points: insights from theory. the American Naturalist (2021)
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Strang, Alexander. Solutions to the Minimum Variance Problem using Delaunay triangulation. SIAM Discrete Mathematics (2020).
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Strang, Alexander. Applications of the Helmholtz-Hodge decompositions to networks and random processes. Case Western Reserve University, Dissertation (2020).
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Calvetti, Daniela, M. Pragliola, E. Somersalo, and A. Strang. Sparse reconstructions from few noisy data: analysis of hierarchical Bayesian models with generalized gamma hyperpriors. Inverse Problems (2019).
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Calvetti, Daniela, E. Somersalo, and A. Strang. Hierarchical Bayesian models and sparsity: l2-magic. Inverse Problems (2019).
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Strang, Alexander, K. C. Abbott, and P. J. Thomas. How to avoid an extinction time paradox. Theoretical Ecology (2019).
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Strang, Alexander, O. Haynes, N. D. Cahill, and D. A. Narayan. Generalized relationships between characteristic path length, efficiency, clustering coefficients, and density. Social Network Analysis and Mining 8 (2018).
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Strang, Alexander, O. Haynes, R. Florez, and D. A. Narayan. Enumerating shortest paths and determining edge betweeness centrality in Cartesian products of paths and cycles. Bulletin of the ICA (2018)
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