Michael Wieck-Sosa
I am a fourth-year PhD student in Statistics at Carnegie Mellon University.
I am very lucky to be advised by Aaditya Ramdas and Cosma Shalizi.
Here is my resume. You can reach me at mwiecksosa AT cmu DOT edu.
My research interests are at the intersection of:
- Causality (invariant causal prediction, conditional independence testing, causal structure learning, mechanism discovery)
- Dependence (high-dimensional time series, time-varying networks, spatiotemporal data, nonlinear stochastic dynamics)
- Machine learning (deep neural networks, transformers, foundation models, large language models)
Research
Statistics journals
- The dynamic generalized covariance measure for conditional independence testing with nonstationary time series (with Michel Haddad and Aaditya Ramdas). Accepted for publication in the Journal of Business & Economic Statistics. arXiv:2504.21647. Slides. Code.
- Estimating dynamic models by matching random features (with Cosma Shalizi). Submitted to the Journal of the Royal Statistical Society, Series B. arXiv:2607.21916. Code.
Machine learning conferences
- Generative sequence modeling for infinite memory processes via predictive states (with Cosma Shalizi). Submitted to ICLR 2027. arXiv:2609.38524.
- Compressed simulation-based inference: neural posterior estimation for massive data via low-dimensional sketches (with Cosma Shalizi). Available upon request.
Interdisciplinary journals
- Dynamic models with p parameters are identified by 2p+1 random features (with Cosma Shalizi). Major revision at Physical Review E. arXiv:2607.16035. Code.
Current projects
- Distribution-uniform anytime-valid inference for time series.
- Anytime-valid invariance testing for time series.
- Model-agnostic simulation-based inference.
- Pretraining large predictive state space models.
News
- June 2026: I gave an invited talk at the 9th International Workshop in Sequential Methodologies (IWSM 2026).
- April 2026: I was awarded the DeGroot-Goel Fellowship for 2026 by the CMU Statistics & Data Science Department faculty.
- April 2026: I successfully proposed my thesis. Topics: generative modeling and dependent data.