| Oct 28, 2026 | CD-Dynamax is now published in the Journal of Open Source Software! Joint work with Matt Levine and Iñigo Urteaga, providing JAX-based tools for continuous-discrete state space modeling and inference. Code. |
| Oct 13, 2026 | The Encanto Neighborhood Field Experiments Dataset: Land–Atmosphere Interactions in Urban Phoenix is now published in Scientific Data! This collaboration brings together observations of Phoenix’s urban microclimate and methods for reconstructing temperature fields. |
| Oct 5, 2026 | Our tutorial, Sequential Inference with Gaussian Processes: A Signal Processing Perspective, is now published in IEEE Signal Processing Magazine! Joint work with Fernando Llorente and Petar Djurić. |
| Oct 2, 2026 | Three new preprints on the arXiv! Wiener-space cubature for nonlinear Gaussian filtering uses tools from rough path theory to derive new, efficient filtering algorithms (led by my amazing intern Luke Snow); simulation-free learning of population dynamics with Wasserstein Lagrangian residuals extends our stitching approach to general Lagrangian actions in population dynamics; and Slaying the Hydra uses tools from actual causality to learn about interactions in large language models. |
| Jun 28, 2026 | Super excited to be in Japan for BAYSM 2026 and ISBA 2026. At BAYSM, I presented dynestyx, which won a Best Poster Award; at ISBA 2026, I’ll present “Online & Predictively-OrientedModel Fusion” in the session on “Calibrated Bayes: Model Design and Adaptation Under Limited Resources” – let me know if you want to grab coffee in Nagoya! |
| Mar 10, 2026 | We’ve publicly released dynestyx, a new library for probabilistic inference of dynamical systems, built on top of NumPyro. |
| Jan 30, 2026 | I’ll be giving a talk titled “Online Bayesian Learning and Ensembles” at the Queens for Computing Colloquium at CUNY Queens College on February 9th! |
| Dec 10, 2025 | I defended my PhD dissertation, “Sequential Bayesian Learning and Ensembles for Online Inference and Experimental Design”! Thank you to my committee members, Yue Zhao, Jorge Mendez-Mendez, and Il Memming Park, and to my advisor, Petar Djurić! |
| Dec 8, 2025 | Designing an Optimal Sensor Network via Minimizing Information Loss (joint work with Fernando Llorente, Katia Lamer, and Petar Djurić) is now accepted by Bayesian Analysis and available on the arXiv! We introduce a novel experimental design framework to leverage varational inference and digital twins in modern sensor placement tasks. |
| Oct 10, 2025 | I had a great time as a research intern at Basis this summer, where I worked with Rafal Urbaniak and Jack Feser on problems in applied Bayesian ML and causality. I’m super excited to join back full-time as a postdoctoral fellow in January 2026, working on tools for dynamical systems with Matt Levine at Basis and Youssef Marzouk at MIT! |
| Dec 7, 2024 | Tangent Space Causal Inference (joint work with Kurt Butler and Petar Djurić) was accepted as a poster at NeurIPS 2024. See you in Vancouver! |