The ACM seminar provides a regular venue for presenting and discussing topics such as numerical analysis, scientific computing, modeling, simulation and visualization. The seminar also hosts regular group meetings and special presentations associated with the NSF-funded RTG program Computation- and Data-Enabled Science (CADES).
Faculty, students and researchers are welcome to attend and present.
Meetings will be held in FHM 462, the large conference room in our department, unless specifically indicated otherwise. Unless specifically stated otherwise, the seminar meeting time will be Fridays at 10:30am.
Notification of upcoming presentations, including Zoom links when relevant, will be sent as calendar invitations to those on our mailing list. To subscribe, click here.
Organizer: Prof. Jeffrey Ovall (jovall@pdx.edu)
Current Seminar Schedule: Spring 2026
April 10 (10:30am): Sergei Pilyugin, University of Florida
Title: Modeling microbial kinetics in a chemostat: some background and applications to bio-clogging
Abstract: In this talk, I will discuss the basic theory of microbial growth in a chemostat, a laboratory device used for continuous growth of microbial cultures, review the history of relevant experimental and theoretical results, and then discuss the recent theoretical developments related to the chemostats with biofilm growth with both constant and variable volume that may help to better understand the problem of bio-clogging.
April 17 (10:30am): RTG Group Meeting
Research updates:
May 1 (10:30am): TBA
May 8 (10:30am): RTG Group Meeting
Research updates:
May 15 (10:30am): Mike Schmidt, Sandia National Laboratory
Title: Lagrangian Random-walk Methods for Fluid Flow on Neuromorphic Hardware
Abstract:
Fluid-flow models are critical to understanding both environmental systems (subsurface groundwater, atmospheric modeling) and to engineering scientific advances (stratospheric aerosol injection, hypersonic flight). Current state-of-the art models are largely Eulerian (grid-based) and have thrived in the era of Moore's Law scaling, advancing in step with our pursuit of exascale computing and beyond. However, we must ask ourselves, "How well do our modeling assumptions align with the physical reality of the systems we wish to study?"
In this talk, we will consider systems and models for which distinct physical processes operate on widely differing scales. This condition is challenging, if not impossible, to capture on models that require a fixed grid discretization. We will discuss Lagrangian (particle-based) methods that solve stochastic differential equations and enable us to resolve large-scale transport properties alongside fine-scale mixing and reactive processes with arbitrarily fine precision. We will also demonstrate the resource efficiency of these methods from a compute and energy-consumption standpoint when employed on neuromorphic computing hardware. It is this final advantage, we contend, that will allow us to continue advancing fluid-flow models as energy resources are restricted and Moore's Law is ended by the physical limits of materials.
Bio:
Dr. Michael Schmidt, completed his PhD in Computational & Applied Mathematics at Colorado School of Mines and is now a research staff member in Computational Sciences at Sandia National Laboratories. There, he works on research-software engineering & development and conducts research on Lagrangian methods for turbulent flows and transport. Outside of research, Mike enjoys spending time with his wife and dogs, traveling in search of good food and wine, coding for home automation, and 3D printing.
May 22 (10:30am): TBA
Title:
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May 29 (10:30am): Kirill Voronin, Nvidia
Title:
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June 5 (10:30am): RTG Group Meeting
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Dates for Fall 2026
October 2
October 9
October 16
October 23
October 30
November 6
November 13
November 20
December 4