Michael Wieck-Sosa

I am a fourth-year PhD Student in the Department of Statistics & Data Science at CMU. I am lucky to be advised by Aaditya Ramdas.

Here is my CV. You can reach me at mwiecksosa AT cmu DOT edu.

My research interests center on statistical and machine learning methods for dependent data. I am especially interested in:

• Time series (high-dimensional, nonstationary, nonlinear, physical dependence, mixingales)
• Causality (structural causal models, invariant prediction, causal discovery, conditional independence testing)
• Machine learning (deep neural networks, transformers, foundation models, large language models)

Research

Under Revision

• Conditional independence testing with a single realization of a multivariate nonstationary nonlinear time series (with Michel F. C. Haddad and Aaditya Ramdas). arXiv.

Working Papers (Available Upon Request)

• Simulation-based estimation of dynamic models by matching random features (with Cosma Shalizi).

Works in Progress

• Goodness-of-fit testing and confidence sets through random features (with Cosma Shalizi).
• Invariant prediction for nonstationary sequences (with Aaditya Ramdas).
• Foundation models for predicting nonstationary sequences (with Aaditya Ramdas).
• Signature methods for large language models (with Leif Weatherby, Tyler Shoemaker, and Cosma Shalizi).