Abstracts
Keynote Speakers:
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J.Nathan Kutz, University of Washington Professor Kutz was awarded the B.S. in Physics and Mathematics from the University of Washington in 1990 and the PhD in Applied Mathematics from Northwestern University in 1994. Following postdoctoral fellowships at the Institute for Mathematics and its Applications (University of Minnesota, 1994-1995) and Princeton University (1995-1997), he joined the faculty of applied mathematics and served as Chair from 2007-2015. Research Interests: Numerical methods and scientific computing, data analysis and dimensionality reduction (PCA, POD, etc) methods, dynamical systems, bifurcation theory, linear and nonlinear wave propagation, perturbation and asymptotic methods, nonlinear analysis, variational methods, soliton theory, nonlinear optics, mode-locked lasers, fluid dynamics, Bose-Einstein condensation, neuroscience, gesture recognition and video & image processing |
Cohort 4 |
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Session 1 |
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| Chantal Baer | Hopping through the interfaces: a multiscale chemo-mechanic model for energy materials |
| Jacob Eller | Applying machine learning to understand photoprotection: how do triazine-based UV-filters really work? |
Session 2 |
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| Arielle Fitkin | Harnessing Molecular Simulations to advance Electronics and Photovoltaics: design rules for the selective deposition of metals by novel condensation techniques |
| Vincent F | Complete thermodynamic description of alloys at extreme pressure and temperature |
Session 3 |
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| Mariia Radova | Optimising power grids and chemical reactions with graph neural networks |
| Joseph DL | Data-driven modelling of irradiation induced defects in fusion materials |
Session 4 |
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| Anson Lee | When the dust settles: predicting deposition of particulate and aerosols |
| Sebastian Dooley | Artificial Intelligence (AI)-enabled Cryogenic Electron Ptychography For Bio-macromolecule Imaging |
Session 5 |
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| Fraser Birks | How amorphous carbon breaks: atomistic models and machine learning |
| Yu Lei | Fundamental physics or data science? Why not both: a data-driven modelling framework for interfacial microflows |
| Hubert Naguszewski | Memory matters: Beyond Markovian models of rare event kinetics |
Cohort 4 |
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Session 1 |
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| Zahra Bhatti | Charting a course towards new light-activated molecules |
| Roman Shantsila | (Inter)facing the Bitter Truth: How to Design Better Interfaces in Next-Gen Batteries using Atomistic Simulations Assisted by Machine-Learning |
| Valdas Vitartas | Machine-learning quantum surrogate models to simulate energy transport across interfaces |
Session 2 |
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| Yuji Go | Complex Electronic Structures for Thermoelectric Energy Materials |
| Philip Jones | What's that made of? Modelling muonic X-ray radiation for quantitative elemental analysis |
| YC Wong | Machine Learning Multiscale Simulation Of Photoconductivity In Correlated Oxides |
Session 3 |
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| Yihui Tong | Developing the capability to forecast extreme Space Weather events |
| Matthew Christensen | Reliable quantum simulations of plasma and fusion physics |
| Minerva Schuler | Alternative protein sources: growing the next generation computational modelling framework |
| Nojus Plunge | Blending ultrasound data with physics-based models to predict damage in structural systems |