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Seminars

Spring 2022

Exploiting parallelism IN LARGE SCALE DEEP LEARNING MODEL TRAINING: FROM CHIPS TO SYSTEMS TO ALGORITHMS

Saurabh Kulkarni
VP and GM, Graphcore (North America)
Presented on: 04/04/2022

GRAPH ENGINE TO TACKLE THE TOUGHEST GRAPH ANALYTICS CHALLENGES

Janice McMahon
Lucata
Presented on: 04/18/2022

This video is password protected and only available to the UIUC Community on Illinois Media Space.

The Cerebras Wafer-Scale Engine (WSE-2) – A new architecture for ML and HPC Workloads

Cindy Orozco Bohorquez & Adam Lavely
Product team Technical Staff, Cerebras
Presented on: 05/02/2022

Fall 2021

Fall21
Ekaterina Gribkova: Evolution of Memory: From Basic Foraging Decisions to Cognitive Map Construction

Evolution of Memory: From Basic Foraging Decisions to Cognitive Map Construction

Ekaterina GribkovaPostdoctoral Research Associate, Coordinated Science Laboratory, University of Illinois Urbana-Champaign11/15/2021
Dan Roberts: PThe Principles of Deep Learning Theory

The Principles of Deep Learning Theory

Dan RobertsResearch Affiliate, Center for Theoretical Physics, Massachusetts Institute of Technology11/08/2021
Machine learning and Inverse Problems in Scientific Imaging

Machine learning and Inverse Problems in Scientific Imaging

Zhizhen ZhaoAssistant Professor, Electrical and Computer Engineering, University of Illinois Urbana-Champaign11/01/2021
Secure Learning in Adversarial Environment

Secure Learning in Adversarial Environment

Bo LiAssistant Professor, Computer Science, University of Illinois Urbana-Champaign10/18/2021
Survival Analysis Based on Survey and Test Data on the UIUC Campus

Survival Analysis Based on Survey and Test Data on the UIUC Campus

Weihao GeResearch Scientist, National Center for Supercomputing Applications, University of Illinois Urbana-Champaign10/11/2021
Looking behind-the-Seen in Order to Anticipate

Looking behind-the-Seen in Order to Anticipate

Alexander SchwingAssistant Professor, Electrical and Computer Engineering, University of Illinois Urbana-Champaign10/04/2021
Domain-guided Machine Learning for Health Analytics

Domain-guided Machine Learning for Health Analytics

Yogatheesan VaratharajahAssistant Research Professor, Bioengineering, University of Illinois Urbana-Champaign09/27/2021
Practical Predictions: Models for Operational Impact

Practical Predictions: Models for Operational Impact

Rebecca SmithAssociate Professor, Veterinary Medicine, University of Illinois Urbana-Champaign09/20/2021

Spring 2021

Spring21
A Startup Foundry Approach to Increasing Research Impact

A Startup Foundry Approach to Increasing Research Impact

Sanjay PatelActing Co-Director IBM-Illinois Center for Cognitive Computing Systems Research, Professor of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign05/03/2021
Dataflow Optimized Systems for AI

Dataflow Optimized Systems for AI

Kunle OlukotunCadence Design Professor of Electrical Engineering and Computer Science, Stanford University04/26/2021
NCSA Industry Overview with Computational Breakthroughs and Synergies with Artificial Intelligence

NCSA Industry Overview with Computational Breakthroughs and Synergies with Artificial Intelligence

Brendan McGinty and Seid KorićDirector of Industry, NCSA and Technical Director, NCSA04/19/2021
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​/Cambridge University​02/22/2021

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