Title: Scalable distributional regression for wearable devices, adjusting for informative non-wear bias (plus hybrid statistical-AI generative models for complex structured data)

Abstract: Many modern instruments (wearables, imaging, geospatial sensors) generate subject-level data streams with thousands to millions or more measurements. Collapsing these to simple summaries (e.g., means) can obscure important structure. We present a general distributional regression framework for distribution-on-scalar and distribution-on-function settings. Distributions are modeled via subject specific empirical quantile functions and represented with quantlet basis functions that provide a compact and near-lossless representation for the subject-specific distributions, enabling joint inference on entire distributions and flexible post hoc computation of any distributional summary to characterize the differences.

Our approach is built on the Bayesian Functional Mixed Model (BayesFMM) framework, accommodating arbitrary mixes of discrete/continuous predictors with smooth (nonlinear) effects, multiple random-effects levels for multilevel designs, nonstationary spatial/temporal dependence, and Gaussian or heavier-tailed errors for robustness. A basis-projection strategy makes the method computationally scalable in both the number of subjects and the number of repeated measurements per subject. Simulation studies show greater efficiency than fitting separate models over a grid of quantiles.

To address informative missingness, we incorporate functional predictors that encode time-of-day non-wear patterns, effectively calibrating each subject’s distribution to a common non-wear profile. Simulations demonstrate that non-wear biases both full-distribution inference and scalar summaries, and we show that our proposed regression calibration approach mitigates this bias more effectively and much more computationally efficiently than imputation.

Applied to the TEAN adolescent accelerometer study, we confirm and refine associations of adolescent activity levels with age, BMI, and walkability, characterizing nuanced effects for these continuous predictors, and identifying which parts of the activity distribution shift without predefining summaries. 

Time permitting, I will briefly preview ongoing work using statistical generative AI to build inferential frameworks for complex object data while preserving key internal structure, with application to handwritten digits data, and show how both the distributional regression for wearable devices and generative AI model for digits data are encompassed by one general methodological framework.

Title: TBA

Abstract: TBA

Title: QED correction to neutron beta decay

Abstract: The neutron lifetime is a key precision observable for testing the Standard Model (SM). A deviation from its predicted value would constitute a clear signal of physics beyond the SM. This talk will briefly review the background of neutron beta decay with a focus on the Fermi function. 

Traditional calculations of the Fermi function are typically restricted to high-$Z$ (atomic number) and small-$\beta$ (velocity) regimes. We introduce a new formalism, deriving a Quantum Field Theory (QFT) analog of the Fermi function that is valid for the low-$Z$ and large-$\beta$ region relevant to neutron decay. 

We will discuss the factorization of this formalism and compute the components of the factorization formula. Furthermore, we will address the resummation and convergence of the associated perturbation theory. Finally, we combine these results to calculate a novel QED correction to the neutron lifetime. We use this updated correction to derive a new, high-precision value for the CKM matrix element $|V_{ud}|$

Title: Overview of the Edwards Accelerator Laboratory and recent activities

Abstract: Ohio University’s Edwards Accelerator Laboratory (EAL) houses a 4.5-MV tandem Pelletron accelerator with six beamlines dedicated to low-energy nuclear science and materials science capabilities. The facility can deliver intense charged particle beams in either direct current or pulsed mode with nanosecond time resolution. End stations include multiple fixed and moveable detection systems for charged particles and gamma rays to study reactions of interest for nuclear structure, nuclear astrophysics, and materials characterization. The laboratory has decades of experience in the production and detection of quasi-monoenergetic and broad-spectrum neutrons up to about 24 MeV for basic science and applications with two beamlines dedicated primarily to neutron work. This talk will give an overview of the EAL, including more detailed descriptions of the neutron production capabilities and characterization methods, highlight recent publications from work conducted in the lab, and describe synergistic activities, including undergraduate research.

Title: The Los Alamos Neutron Electron Dipole Moment (LANL nEDM) Experiment

Abstract: Experimental searches for the neutron electric dipole moment (nEDM) provide sensitive probes into CP-violating physics. The Los Alamos Neutron Electric Dipole Moment Experiment (LANL nEDM) aims to measure the neutron EDM with a statistical uncertainty of 2x10^-27 e-cm in a year-equivalent of data collection using Ramsey’s method of separated oscillatory fields at the recently upgraded ultracold neutron (UCN) facility. A description of the apparatus and the current status will be reported with a particular focus on the magnetic field system.

Title: QCD and QED Radiation in Lepton-Hadron Scattering: A Joint Factorization Approach

Abstract: The factorization theorem plays an important role in the analysis of high energy quantum chromodynamic (QCD) processes, separating the nonperturbative hadronic interaction into the universal parton distribution functions (PDFs) and fragmentation functions (FFs) and the process-dependent interactions into short distance perturbative calculations, with any interference power suppressed. With a virtual photon exchange, lepton-hadron deep inelastic scattering (DIS) provides an electromagnetic hard probe for the partonic structure of colliding hadrons and has played an important role in the development of QCD factorization.  However, the collision induced QED radiation can change the momentum of the exchanged but unobserved virtual photon, making the photon-hadron frame, where the factorization formalism for DIS and semi-inclusive DIS (SIDIS) was derived, ill defined. A new analogous factorization approach has been introduced to separate the leading power process-independent QED radiative contributions to the single photon exchange by introducing lepton distribution functions (LDFs) and lepton fragmentation functions (LFFs), while process-dependent effects are perturbatively calculated with large logarithms removed [J. High Energ. Phys. 2021, 157 (2021)]. These LDFs and LFFs are considered global, as they appear in many different interactions, such as $e^+ e^-$, DIS and SIDIS, so data from experiments can be used to fit and describe these functions across a wide range of lepton scattering. In this work, I will apply this new hybrid factorization approach to lepton-hadron DIS and SIDIS. For DIS, I derive the NLO short distance perturbative contribution to the cross section and demonstrate the effects the QED radiation has on the cross section using this approach using the CTEQ parameterization for the QCD functions. As part of the SIDIS analysis, I study the cross-section in two different kinematic regions: (1) the scattered lepton and observed hadron are not near back-to-back, and (2) they are close to back-to-back, where collinear QCD factorization works for (1) and TMD QCD factorization for (2) while collinear QED factorization works for both. As part of this work, I show the effects on the SIDIS cross section using fixed order calculations for the unpolarized structure function by first showing the effect of the radiative corrections on the main kinematic variables, especially how the internal transverse momentum is significantly correlated to the external angular dependence, and then the unpolarized structure function (or cross section) with matching between the descriptions for low and high transverse momentum. This work will impact the calculations for predictions for data from COMPASS and various Jefferson Lab experiments.