Michael W. Trosset
Computer Science · Indiana University
Publications
111
Citations
4,198
Est. group size
—
Recurring co-author estimate
Active years
40
Publishing since 1987
Michael W. Trosset works at the intersection of statistics and computer science, developing mathematical methods for analyzing complex data such as networks (graphs) and high-dimensional measurements. Much of his work focuses on techniques that represent data as points in geometric spaces (embeddings) and on drawing reliable statistical conclusions from these representations. He also contributes to optimization methods used to fit and estimate statistical models.
Publication activity has been steady over the last decade at roughly two to three papers per year, with an uptick in the most recent years.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Michael Trosset’s contribution to the Discussion of ‘Statistical exploration of the Manifold Hypothesis’ by Whitely et al.
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 2026
- Out-of-Sample Embedding with Proximity Data: Projection Versus Restricted Reconstruction
Journal of Computational and Graphical Statistics · 2026
- Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings
Journal of Computational and Graphical Statistics · 2026
- Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings
Figshare · 2026
- Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings
Figshare · 2026
- Convergence Guarantees for Response Prediction for Latent Structure Network Time Series
IEEE Transactions on Network Science and Engineering · 2025
- Out-of-Sample Embedding with Proximity Data: Projection versus Restricted Reconstruction
arXiv (Cornell University) · 2025
- Continuous Multidimensional Scaling
arXiv (Cornell University) · 2024
- Consistent estimation of generative model representations in the data kernel perspective space
arXiv (Cornell University) · 2024
- Optimizing the Induced Correlation in Omnibus Joint Graph Embeddings
arXiv (Cornell University) · 2024
- Semisupervised regression in latent structure networks on unknown manifolds
arXiv (Cornell University) · 2023
- Semisupervised regression in latent structure networks on unknown manifolds
Applied Network Science · 2023
- Popularity Adjusted Block Models are Generalized Random Dot Product Graphs
Journal of Computational and Graphical Statistics · 2022
- Popularity Adjusted Block Models are Generalized Random Dot Product Graphs
Figshare · 2022
- Algorithm 1007
ACM Transactions on Mathematical Software · 2020
- arXiv (Cornell University)×12
- Journal of Computational and Graphical Statistics×4
- Figshare×4
- ACM Transactions on Mathematical Software×1
- IEEE/ACM Transactions on Computational Biology and Bioinformatics×1
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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