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Seminars

Spring 2021

Spring21
Data Science and the Valley of Death! How the National Labs Help You Bridge the Gap

Data Science and the Valley of Death! How the National Labs Help You Bridge the Gap

Wayne MillerDeputy Director, Lawrence Livermore National Laboratory04/12/2021
Tensor Methods for Deep Learning with TensorLy and PyTorch

Tensor Methods for Deep Learning with TensorLy and PyTorch

Jean KossaifiSenior Research Scientist, NVIDIA04/05/2021
AI for Food Security

AI for Food Security

Sebastian AhnertSenior Research Fellow and Lecturer, The Alan Turing Institute and University of Cambridge03/22/2021
So You Built an AI Model, Now What?

So You Built an AI Model, Now What?

Brian MartinResearch Fellow, Head of AI, R&D IR, AbbVie03/08/2021
A Shared-memory Approach to Big Data and Analytics

A Shared-memory Approach to Big Data and Analytics

Peter HoftseeResearch Staff Member, IBM03/01/2021
Data Science and Historical Texts: Modeling Meaning Change from Ancient Greek to Web Archives

Data Science and Historical Texts: Modeling Meaning Change from Ancient Greek to Web Archives

Barbara McGillivrayResearch Fellow, The Alan Turing Institute‚Äč/Cambridge University‚Äč02/22/2021

Fall 2020

Fall20
Data Heterogeneity and Disease Surveillance: Impacts on Precision and Accuracy

Data Heterogeneity and Disease Surveillance: Impacts on Precision and Accuracy

Rebecca SmithAssistant Professor, University of Illinois at Urbana-Champaign11/16/2020
Chemical Imaging for an Expanded View of the Pathologic Basis of Disease: A Challenge for AI

Chemical Imaging for an Expanded View of the Pathologic Basis of Disease: A Challenge for AI

Rohit BhargavaProfessor, University of Illinois at Urbana-Champaign11/09/2020
Demystifying Hardware Acceleration for Machine Learning

Demystifying Hardware Acceleration for Machine Learning

Matthew KrafczykResearch Programmer, National Center for Supercomputing Applications11/02/2020
Topological Obstructions to Autoencoders

Topological Obstructions to Autoencoders

Yoni KahnAssistant Professor, University of Illinois at Urbana-Champaign10/26/2020
The Geometry of Data: An Interpretation of the Challenges of Training Models at Scale

The Geometry of Data: An Interpretation of the Challenges of Training Models at Scale

Aaron SaxtonData Engineer, National Center for Supercomputing Applications10/19/2020
Convolutional Tensor-Train LSTM for Spatio-Temporal Learning

Convolutional Tensor-Train LSTM for Spatio-Temporal Learning

Wonmin ByeonResearcher, NVIDIA10/12/2020
Machine Learning for Quantum Computing and Quantum Matter

Machine Learning for Quantum Computing and Quantum Matter

Bryan ClarkAssistant Professor, University of Illinois at Urbana-Champaign10/05/2020
Design and Control of Soft Musculoskeletal Architectures

Design and Control of Soft Musculoskeletal Architectures

Mattia GazzolaAssistant Professor, University of Illinois at Urbana-Champaign09/21/2020
End-to-End Issues in AI: Challenges and Research Opportunities video

End-to-End Issues in AI: Challenges and Research Opportunities

Rajaram KrishnamurthyTechnical Staff Member, IBM Systems09/14/2020