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.
The Scientific Computing and Data Science Seminar has temporarily merged with the Energy and Environment Seminar. It can be taken for course credit as Math 293-03.
The merged seminar will, for now, be known as the Data Energy Environment Scientific COmputing seminar or DEESCO seminar.
For the Fall 2026 semester, seminars will take place on Tuesdays from 10:30am to 11:20am in ACS 362B. If there is a need for it, we will establish a remote option as well.
Contact Harish Bhat (hbhat@ucmerced.edu) or Andy Wan (andywan@ucmerced.edu) for more information or to register to the class.
Schedule for Fall 2026:
September 1: Organizational meeting
September 8: No seminar because of Department Colloquium
September 15: Harish Bhat, Applied Mathematics Professor
September 22: Saleha Begum, Applied Mathematics Graduate Student
September 29: Harish Bhat, Applied Mathematics Professor
October 6: Jeremy Mathew and Yash Deodhar, Applied Mathematics Graduate Students
October 13: Pratham Lalwani, Applied Mathematics Graduate Student
October 20: John Gallagher and Satinder Singh, Applied Mathematics Graduate Students
October 27: No seminar because of the SIAM NCC meeting
November 3: Yuxiang Feng, Applied Mathematics Graduate Student
November 10: Saket Kharki and Kendra Calman, Applied Mathematics Graduate Students
November 17: Antonia Peters, Applied Mathematics Graduate Student
November 24: No seminar, early Thanksgiving celebration
December 1: Andy Ponce, Applied Mathematics Graduate Student
December 8: TBD
Schedule for Spring 2026:
January 21: Organizational meeting
January 28: Pat Sprenger, Applied Mathematics Postdoc
February 4: François Blanchette, Applied Mathematics Professor
February 11: Joseph Simpson, Applied Mathematics Graduate Student
February 18: Moitrish Majumdar, Applied Mathematics Graduate Student
February 25: Pablo Curiel, Applied Mathematics Graduate Student
March 4: Interview Preparation discussion led by François Blanchette, Applied Mathematics Professor
March 11: Antonia Peters, Applied Mathematics Graduate Student
March 18: Satinder Singh and Kevin Collins, Applied Mathematics and Physics Graduate Students
March 25: Spring Break
April 1: Hannah Love, Applied Mathematics Graduate Student
April 8: Mohammed Sharif and Bradley Yount, Mechanical Engineering and Applied Mathematics Graduate Students
April 15: Saket Kharki and Kendra Calman, Applied Mathematics Graduate Students
April 22: Jeremy Mathew and Yash Deodhar, Applied Mathematics Graduate Students
April 29: Internship applications and Grant writing discussion led by Juan Meza, Applied Mathematics Professor
May 6: John Gallagher and Pratham Lalwani, Applied Mathematics Graduate Students
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
