Arizona-Los Alamos Days 2022
THIS EVENT HAS BEEN POSTPONED TO FALL, 2022 DUE TO THE WILDFIRE CONDITIONS IN LOS ALAMOS, NM. MORE DETAILS COMING SOON...
On May 16-17, 2022, the Program in Applied Mathematics will host the Los Alamos - Arizona Days Conference. The event will be held in person at the Center for Nonlinear Studies at Los Alamos National Lab
There will be 4 topic sessions: Computer and Data Science, Fluid Mechanics, Materials Science, and Biological Applied Math
The tentative schedule is as follows:
| Topic / Time Speaker (affiliation) |
Title of talk / abstract | |
|---|---|---|
|
Monday, May 16, 2022 |
||
| 7:00-9:00am |
UArizona participants are getting badges @ Badge Office |
|
| SESSION 1: COMPUTER & DATA SCIENCE 9:00-12:15pm |
DANIEL BURRILL, NATALIE KLEIN, NISHANT PANDA (LANL) & MICHAEL "Misha" CHERTKOV (UA) | |
| 9:00-9:15 Welcome | Welcome from LANL and UA managers | |
| 9:15-9:50 Michael "Misha" Chertkov (UA) | Graph and Agent Models of Pandemics (Viral and Social) | |
| 9:50-10:10 Michael Tynes (LANL) | Getting the Most out of Molecular Fingerprints: Methods for Fast and Interpretable Prediction from Raw Molecular Substructures | |
| 10:10-10:30 Dan Van Boxel (UA) | Born in a BARN: Bayesian Additive Regression Network | |
| 10:30-10:45 | 15 minute break | |
| 10:45-11:05 Kellin Rumsey (LANL) | A hierarchical, sparse Gaussian process for in situ inference in expensive physics simulations | |
| 11:05-11:25 Michael Kuser (LANL) | On visual self-supervision and its effect on model robustness | |
| 11:25-11:45 Natalie Klein (LANL) | Learning data shifts in spectroscopy via structured normalizing flows | |
| 11:45-12:05 Laurent Pagnier (UA) | Physics Informed Machine Learning for Model Reduction in Power System | |
| 12:05-12:15 TBD | Discussion of the future collaborations in the area of AI/ML/Data/CS | |
| 12:15-1:30pm | Lunch Break | |
| SESSION 2: FLUID MECHANICS 1:30-4:45pm |
VITALY GIRYA (LANL) & LAURA MILLER (UA) | |
|---|---|---|
| 1:30-2:00 Charles Wolgemuth (UA) | Filaments, suspensions, and microorganism motility | |
| 2:00-2:30 Laura Miller (UA) | Multiscale flow around sea fans | |
| 2:30-3:00 Sidharth, GS (LANL) | TBD | |
| 3:00-3:15 | 15 minute break | |
| 3:15-3:45 Filipe Pereira (LANL) | TBD | |
| 3:45-4:15 Ismael Boureima (LANL) | TBD | |
| 4:15-4:30 Michael Woodward (UA) | Physics Informed Machine Learning with Smooth Particle Hydrodynamics: Machine Learning Lagrangian Turbulence | |
| 4:30-4:45 Criston Hyett (UA) | Machine Learning Lagrangian Tetrads: Reduced-Order Modeling of Turbulence | |
Tuesday, May 17, 2022
| SESSION 3: materials science 9:00-12:15pm |
kipton barros, sergei tretiak (LANL) & marat latypov (UA) | |
|---|---|---|
| Reeju Pokharel (LANL) | Machine learning for accelerated microstructure characterization | |
| Ben Nebgen (LANL) |
Machine Learning Parameterized Hamiltonians for Intuitive Quantum Chemistry Models |
|
| Marat Latypov (UA) | Machine learning mechanical properties in relation to heterogeneous mesoscale microstructure | |
| Javier Estrada (LANL) |
Learning a General Model of Fluid Flow in Complex Porous Media from Large 3D arrays |
|
| 15 minute break | ||
| Patrick Lohr (UA) | Atomistic Insights into the Thermomechanical Properties of Perovskite Thin-Film | |
| Jessica Lalonde (LANL) | Machine Learning for Predicting Chemistry- and Environment-Dependent Degradation Behavior of Biopolymers | |
| Kyler Novotny (UA) | Understanding slip activity and void initiation in metals using machine learning-based microscopy analysis | |
| Michael Taylor (LANL) |
Bringing data-driven strategies to f-block chemistry from experiments and theory |
|
| 12:15-1:30PM | Lunch Break | |
| SESSION 4: BIOLOGICAL APPLIED MATH 1:30-4:45Pm |
eMMA GOLDBERG (LANL) & kEVIN LIN (UA) | |
|---|---|---|
| 1:30-1:50 Alexa Aucoin (UA) | Detecting functional subnetworks in primate amygdala | |
| 1:50-2:10 Avinash Karamchandani (UA) | TBD2 | |
| 2:10-2:30 Matea Santiago (UA) |
Simulations of Chemical Concentration around Pulsing Soft Corals |
|
| 2:30-2:50 Kelly Heilman (UA) | Quantifying uncertainty around forest carbon storage and uptake: a Bayesian state-space model approach | |
| 2:50-3:10 Kevin Lin (UA) | A principled approach to mapping cortical parameter space | |
| 3:10-3:25 | 15 minute break | |
| 3:25-3:45 Tin Phan (LANL) |
Modeling viral resistance to monotherapy with monoclonal antibody treatment for SARS-CoV-2 |
|
| 3:45-4:05 Julie Spencer (LANL) |
Distinguishing viruses responsible for influenza-like illness |
|
| 4:05-4:25 Anastasia Kim (LANL) |
LDA topic modeling and Bayesian network analysis on plant-microbiome data |
|
| 4:25-4:45 Migun Shakya (LANL) |
Soil virome |
|
| 4:45-5:05 Zach Fox (LANL) | TBD | |
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Main organizers are (Nick Hengartner/LANL, Enrique Batista/LANL - Misha Chertkov/UA).
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Organizers of the topical sessions are:
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Computer & Data Science (DANIEL BURRILL, NATALIE KLEIN, NISHANT PANDA (LANL) & MISHA CHERTKOV (UA)
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Fluid Mechanics (VITALY GIRYA (LANL) & LAURA MILLER (UA)
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Materials Science (KIPTON BARROS, SERGEI TRETIAK (LANL) & MARAT LATYPOV (UA)
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Biological Applied Math (EMMA GOLDBERG (LANL) & KEVIN LIN (UA)
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If you are interested to present a short talk or a poster session please get in contact with leaders of the respective session ASAP.