We work on problems at the interface of stochastic analysis, statistical mechanics, and scientific computation. Application areas include soft condensed matter physics and biophysics. We also work on general methods in numerical analysis and machine learning.
We gratefully acknowledge the following sources of support: *This material is based upon work supported by the National Science Foundation under Grant No. NSF DMS-0635535 and NSF CAREER DMS-0956210. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).
GMLS-Nets: Neural Networks for Scattered Data Sets
GMLS-Nets: A Framework for Learning from Unstructured Data, N. Trask, R. G. Patel, B. J. Gross, and P. J. Atzberger, arXiv:1909.05371, (2019), [paper].
Postdoctoral Position Available in Scientific Computation and Machine Learning.
Funding has become available for a new postdoctoral position concerning research on machine learning methods and related approaches in scientific computation. To apply, please see link here. Some additional information can be found in position paper and recent UC Current Article.
June 2019: Congratulations to David Rower!
Congratulations to David Rower on acceptance to Massachusetts Institute of Technology (MIT), selection for National Science Foundation (NSF) Graduate Student Fellowship, and receiving UCSB Physics Research Excellence Award!
June 2018: Congratulations to Ben Gross on Ph.D. and Graduation!
September 2018: Awarded by the US Department of Energy a collaborative grant as part of MMICCs initiative for machine learning and scientific computation.
The grant provides support for research at UCSB and collaborative activities with researchers at Sandia National Laboratories (SNL), Pacific Northwestern National Laboratories (PNNL), and Stanford, Brown, and MIT. Additional information: [PDF][UC Current Article].
August 2018: David Rower and Ben Gross attending and giving research talks at SIAM Conference in Minneapolis, MN.
June 2016: Summer School on Multiscale Modeling of Materials CM4 (Stanford University, June 20-23, 2016)
The workshop focuses on mathematical modeling of soft materials and computational methods. We present a tutorial on fluctuating hydrodynamics approaches and our computational package SELM for simulations using the LAMMPS molecular dynamics software.
Software package SELM for fluctuating hydrodynamics simulations in LAMMPS [software website]
June 2016: Soft Matter Journal highlights on the cover our work on curved fluid interfaces.
This research is reported in the paper
Hydrodynamic Coupling of Particle Inclusions Embedded in Curved Lipid Bilayer Membranes, J.K. Sigurdsson and P.J. Atzberger, 12, 6685-6707, Soft Matter, The Royal Society of Chemistry, (2016) [paper] .
June 2013: Gil Tabak gives CCS Commencement Speech.
December 2012: Software Package Mango-Selm for fluctuating hydrodynamics thermostats has been released!
This is available as part of the Lammps Molecular Dynamics Software (Sandia, DOE). The package allows for dynamic simulations of implicit-solvent coarse-grained models using SELM thermostats. [more information].
December 2012: Awarded from US Department of Energy a collaborative grant to found a MMICCs center on Computational Methods for Soft Materials (CM4).
The grant will provide support for research at UCSB and collaborative activities with researchers at Sandia National Laboratories (SNL), Pacific Northwestern National Laboratories (PNNL), and Stanford, Brown, Penn State, and MIT. Additional information: [CM4 MMICCs Center].
July 2012: David Valdman successfully defends his thesis!
Congratulations to Dr. Valdman!
April-June 2012: KITP Workshop :
Physical Principles of Multiscale Modeling, Analysis and Simulation in Soft Condensed Matter, Coordinators: Paul J. Atzberger, Kurt Kremer, Mark Robbins [link]
June 2011: Daniel Kerr gives CCS Commencement Speech.