Journal:
Numerical methods for computing the discrete and continuous Laplace transforms. IMA Journal of Applied Mathematics. 2024 (arxiv preprint version)
Group-Invariant Machine Learning on the Kreuzer-Skarke Dataset, Physics Letters B, 2024
Applications of Deep Neural Networks with Fractal Structure and Attention Blocks for 2D and 3D Brain Tumor Segmentation, Journal of Statistical Theory and Practice (Statistics and Deep Learning special issue), 2024
Kimesurface Representation and Tensor Linear Modeling of Longitudinal Data, Neural Computing and Applications Journal. 2022
Determinism, Well-posedness, and Applications of the Ultrahyperbolic Wave Equation in Spacekime. Partial Differential Equations in Applied Mathematics. 2022
Conferences:
Best Student Paper Award by American Statistical Association (AmStat) - Statistical Methods in Imaging (SMI) Conference (Theory and Methods). Statistical foundations of invariance and equivariance in deep artificial neural network learning. 2024
Preprint:
Towards a framework on tabular synthetic data generation: a minimalist approach: theory, use cases, and limitations. Summer internship project with Agus Sudjianto, Nengfeng Zhou and Wells Fargo CMOR team.
Presentations:
Statistical Foundations of Invariance and Equivariance in Deep Artificial Neural Network Learning, Statistics Methods in Imaging, 2024 May, slides
Spacekime Analytics (SciFM), University of Michigan, 2024 April, poster
Invariance and equivariance in deep network learning: mathematical representation, probabilistic symmetry, Variable Exchangeability, and Sufficient Statistics, Americal Physical Society East Great Lake Section, 2023 Oct, pdf
Numerical Methods and Analysis for Computing Forward and Inverse Laplace Transform For discrete and continuous signals, APS April Meeting, 2023 April, pdf
Laplace Transform and Inverse Laplace Transforms - Numerical Methods, Groups, and Clifford Algebra, Americal Physical Society East Great Lake Section, 2022 Oct, pdf
Wheeler Dewitt Equation in Spacekime, 2021 Oct, pdf