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USACM Webinar. UQ and Prob. modeling TTA. Title: Managing Uncertainty and Credibility Assessments for Epidemiology Exascale Agent Based Models

April 25; 3 pm EDT

Speaker: Erin Acquesta, Sandia National Laboratories

Title: Managing Uncertainty and Credibility Assessments for Epidemiology Exascale Agent Based Models

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USACM-Webinar. TTA-UQ and Prob. Modeling. Title: Sampling and generative modeling using dynamical representations of transport by Youssef Marzouk

This is a reminder that our next monthly webinar is March 20, 3-4pm EDT. The speaker will be Youssef Marzouk from Massachusetts Institute of Technology. 

Speaker: Youssef Marzouk, Massachusetts Institute of Technology 

Title: Sampling and generative modeling using dynamical representations of transport

 

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USACM-Webinar. TTA-UQ and Prob. Modeling. Title: Uncertainty Quantification and Generative Modeling Using Multi-fidelity Strategies, Speaker: Alireza Doostan

Monthly Webinar. TTA-Uncertainty Quantification and Probabilistic Modeling.

February 13; 3 pm - 4pm EST

Speaker: Alireza Doostan, University of Colorado, Boulder

Title: Uncertainty Quantification and Generative Modeling Using Multi-fidelity Strategies

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Invitation to MS - Recent Trends in Data-Driven and Computational Modeling of Materials Across Scales: From First Principles Calculations to Mesoscale Physics, at USNCCM18, 2025

Dear Colleagues, 

We are organizing a mini-symposium 801 - Recent Trends in Data-Driven and Computational Modeling of Materials Across Scales: From First Principles Calculations to Mesoscale Physics, at USNCCM18, July 20–24, 2025, Chicago. We invite you to submit an abstract at this symposium. The abstract submission deadline is January 15, 2025. Please find the submission portal here:  https://usnccm18.usacm.org/abstract-submission        

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Webinar, USACM, TTA-Uncertainty Quantification and Probabilistic Modeling:: Title: Measuring dataset similarity in clustering-based, uncertainty-aware federated learning. Speaker: Prof. Chao Hu, University of Connecticut

This is a reminder that our next monthly webinar is December 5, 3-4pm EST. The speaker will be Associate Professor Chao Hu from University of Connecticut. We are hoping the format will promote a lively interactive discussion and engage both junior and senior members of our community. Look forward to seeing you there.

Monthly Webinar by USACM, TTA-Uncertainty Quantification and Probabilistic Modeling

December 5; 3pm EST

Speaker: Associate Professor Chao Hu, University of Connecticut

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Webinar:: Title: Foundational models for materials chemistry, Speaker: Prof. Gábor Csányi, University of Cambridge

Monthly Webinar: USACM, TTA-Nanotechnology and Lower Scale Phenomena

This is a reminder that our next monthly webinar is November 27, 2-3pm CST. The speaker will be Professor Gábor Csányi from the University of Cambridge. We are hoping the format will promote a lively interactive discussion and engage both junior and senior members of our community. Look forward to seeing you there. Talk and discussions will be archived and available on our website if accepted by the speaker.

November 27; 2pm CST

Speaker: Prof. Gábor Csányi, University of Cambridge

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USACM: UQ TTA Webinar. Starting soon. Title: Multifidelity linear regression for scientific machine learning from scarce data

This is a reminder that our next monthly webinar is October 10, 3-4pm ET, is starting soon. 

Monthly Webinar

October 10; 3pm ET

Speaker: Elizabeth Qian, Georgia Tech

Title: Multifidelity linear regression for scientific machine learning from scarce data

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USACM Nano-Scale TTA Webinar. Title: More than physics, more than data: Integrated machine-learning models for materials

Our speaker will be Prof. Michele Ceriotti from EPFL.

We look forward to seeing you there.

Date/Time: September 25; 2-3pm CST

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USACM Nano-Scale TTA Webinar by Prof. Gideon Simpson

 

Join Zoom Meeting: (https://us06web.zoom.us/j/84541274013?pwd=ZDhuM09BaUlVVlBuREhEV0sweGFlZz09: Meeting ID: 845 4127 4013/Passcode: 799065)

 

Date/Time: February 28; 2-3pm CST

Speaker: Gideon Simpson, Drexel University

Discussant: Petr Plechac, University of Delaware

 

Title: Learning dynamics with random Fourier features

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USACM Nano-Scale TTA Webinar by Prof. Surya R. Kalidindi

USACM Nanotechnology and Lower Scale Phenomena TTA,  webinar is on Jan 31, at 2-3 pm central time.

Speaker: Prof. Surya R. Kalidindi from Georgia Institute of Technology

We have Prof. Raymundo Arróyave of Texas A&M University as the discussant.

We are hoping the format will promote a lively interactive discussion and engage members of our community. We look forward to seeing you there.  Please forward this to anyone who may be interested.

Join Zoom Meeting

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USACM Nanotechnology and Lower Scale Phenomena TTA, Webinar by Dr. Timofey Frolov

Next USACM Nanotechnology and Lower Scale Phenomena TTA,  webinar is on December, 6 at 2pm central.

Our speaker will be Dr. Timofey Frolov from Lawrence Livermore National Laboratory, with Prof. Fadi Abdeljawad, Lehigh University as the discussant.
We are hoping the format will promote a lively interactive discussion and engage both junior and senior members of our community.

We look forward to seeing you there.

Date/Time: December 6; 2-3pm CST

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Ph.D. position on Machine Learning and Computational Materials Modeling, Mechanical Engineering at the Michigan Tech, starting August 2024

Please forward this message to anyone who you feel might be interested in this position. 

We are looking for a self-motivated Ph.D. student to study Machine Learning enabled computational models for applications in Material Modeling and Computational Mechanics, starting August 2024. This project will draw ideas from various subjects including Bayesian Machine Learning, Scientific Machine Learning, Projection-based model reduction, Computational Mechanics, and Medical Imaging. This is a collaborative project between Michigan Tech and University of California, Los Angeles.

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USACM Nanotechnology Virtual Seminar by Kaushik Bhattacharya. 09/27; 2-3pm CDT;

Our upcoming webinar is on September 27 at 2pm central.

Date/Time: September 27; 2-3pm CDT

Join via Zoom: https://us06web.zoom.us/j/84541274013?pwd=ZDhuM09BaUlVVlBuREhEV0sweGFlZz09

(Meeting ID: 845 4127 4013/Passcode: 799065)

Speaker: Kaushik Bhattacharya, California Institute of Technology

Discussant: Miguel Bessa, Brown University

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Jensen-Shannon Divergence Based Novel Loss Functions for Bayesian Neural Networks

The Kullback-Leibler (KL) divergence is widely used in state-of-the-art Bayesian Neural Networks (BNNs) to ap- proximate the posterior distribution of weights. However, the KL divergence is unbounded and asymmetric, which may lead to instabilities during optimization or may yield poor generalizations. To overcome these limitations, we examine the Jensen-Shannon (JS) divergence that is bounded, symmetric, and more general. Towards this, we propose two novel loss functions for BNNs.

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Funded Ph.D. position on Machine Learning, Mechanical Engineering at the Michigan Tech

Funded Ph.D. position in the Department of Mechanical Engineering- Engineering Mechanics at the Michigan Technological University. Starting June/September 2023. 

Kindly forward this message to anyone who you feel might be interested in this position. 

We are looking for a self-motivated Ph.D. student to study Machine Learning enabled computational models for applications in Material Modeling and Computational Mechanics. 

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