We intend the terms scientific computing and data science to be broadly defined and inclusive. Topics of interest include but are not limited to:

- Novel numerical methods, numerical analysis, high-performance computing, parallel algorithms, and application problems that involve numerical challenges.
- Machine learning algorithms, deep learning and neural networks, applied/predictive modeling with real-world data, data-enabled science, dimensionality reduction, Bayesian methods, natural language processing, and computational statistics.

During Fall 2024, we will meet on **Thursdays, 3:00-4:00pm** in **ACS 362B**.

This seminar is part of the RTG theme “Scientific Computing and Data Science”. If you have questions, please contact Prof. Changho Kim (ckim103@ucmerced.edu).

### Schedule Fall 2024

**Aug 29**: Organizational meeting**Sep 12**: Andy Wan - Bayesian Inference for dynamical systems - Part I**Sep 19**: Scott West - Mesh free interpolation of initial conditions on octree grids**Oct 3**: Adam Binswanger - Numerical simulations of incompressible multi-phase fluid flows**Oct 17**: Alex Villa - Better tasks for task Based parallelism in multiphysics framework**Oct 31**: Hardeep Bassi - Ground state energy estimation from noisy quantum observables**Nov 7**: Alex Ho**Nov 14**: Tanya Tafolla**Nov 21**: Andy Wan**Dec 5**: Matthew Blomquist - Characteristic bending**Dec 12**: Cole Cooper

### Schedule Spring 2024

**Jan 24**: Organizational meeting**Feb 7**: [Discussion] How to do machine-learning research**Feb 14**: Harish Bhat - How to Write a Research Proposal**Feb 21**: Changho Kim - Brief overview of different Monte Carlo approaches**Feb 28**: Maia Powell - Utilizing satellite data for groundwater analysis**Mar 6**: Hardeep Bassi - A time-delay scheme for the propagation of reduced 1 electron density matrices and the effect of memory**Mar 13**: Joseph Simpson - 2D synthetic aperture radar imaging of extended targets**Mar 20**: [Discussion] How to use the Pinnacles cluster**Apr 3**: Adam Binswanger - Collocated numerical simulations of incompressible fluid flows**Apr 10**: Alex Nguyen - Nyström type exponential integrators for strongly magnetized particle pushing problems**Apr 17**: Matt Blomquist - Gaussian process regression for the estimation of two-dimensional interface curvature**Apr 24**: Zihan Xu - Developing statistics-informed neural network as a robust and computationally efficient surrogate modeling tool**May 1**: [Discussion] Planning for the next semester**May 2 THR, 11:30am - 12:30pm**: Dr. Andy Nonaka (LBNL)

### Schedule Fall 2023

**Aug 24**: Kick-off meeting**Aug 31**: Zihan Xu - Extension of Statistics-informed Neural Network to Multi-dimensions with Self-Adaptive Loss Balancing for Enhanced Performance**Sep 7**: Adam Binswanger - Stable nodal projection method on quadtree grids for incompressible, multi-phase fluid flows**Sep 14**: Alex Nguyen - A Runge-Kutta-Nyström type exponential integrator with an application to numerically simulate strongly magnetized charged particle dynamics**Sep 22**(Friday, 2pm, ACS 362B): Hong Zhang (ANL) - PETSc Library and its Application to the Multiphysics Simulation over Networks**Sep 28**: Discussion (programming skills)**Oct 5**: Harish Bhat - Machine learning for the time-dependent Hartree-Fock equation**Oct 19**: Scott West - Nodal Projection Methods for Incompressible Fluid Flows**Nov 9**: Andy Wan - Bayesian inference using Hamiltonian Monte Carlo**Nov 30**: Kevin Collins - Vortices and the shape of flow