Daniel T. Chen

Research

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I am broadly interested in applied probability, but I specialize in stochastic analysis and interacting particle systems, particularly limit theory and adjacent graph-theoretic concerns. I’ve also applied probabilistic methods to machine learning, signal processing, mathematical biology, quantum networks, and quantum algorithms. I am also actively working on some of the mathematical foundations of AI; stay tuned for updates.

Below is a selected list of my published work, organized in terms on topics (coauthors listed in alphabetical order unless specified). For a complete, chronological ordered (and automatically updated) list, see my Google Scholar profile.

Interacting particle systems on sparse networks

High-dimensional stochastic dynamics on sparse networks (working papers with Kavita Ramanan and Ankan Ganguly). Code.
*Outstanding Student Poster Award at the Stochastic Networks Conference 2026.

Machine Learning and signal processing

A variational framework for residual-based adaptivity in neural PDE solvers and operator learning (with Juan D. Toscano, Vivek Oommen, Jerome Darbon, George Em Karniadakis). NPJ Artificial Intelligence (2026). Journal. ArXiv.
Explicitly solvable continuous-time inference for partially-observed Markov processes (with Andrew W. Eckford, Alexander G. Strang, and Peter J. Thomas). IEEE Transactions on Signal Processing (2022). Journal. Arxiv.

Sequential decision-making

Dynamic decision-making under model misspecification: A stochastic stability approach (with Xinyu Dai and Yian Qian). Preprint (2026). Arxiv.

Mathematical Biology

Capacity of a class of fully observed multistate Poisson-type signal transduction channels (with Andrew W. Eckford, and Peter J. Thomas). IEEE International Symposium on Information Theory (2025). Conference.

Quantum Algorithms and Networks

Inferring quantum network topology using local measurements (with Brian Doolittle, Eric Chitambar, Jeffrey Larson, and Zain H. Saleem). PRX Quantum (2023). Journal. Arxiv. Code.
Quantum circuit cutting for classical shadows (with Michael A. Perlin and Zain H. Saleem). ACM Transactions on Quantum Computing(2024). Journal. Arxiv
Online detection of golden circuit cutting points (with Ethan Hansen, Shuai Xu, and others). IEEE Conference on Quantum Computing and Engineering (2023). Conference. Arxiv.