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November 16 | Virtual & Free

SigOpt AI & HPC Summit 2021


Panel: Best Practices for Experiment Design

2 - 2:45pm

Models are only as effective as the design of experiments that evaluate, compare, test and validate them. Between real-world constraints, limitations of your computing environment, and everything in between, there are many decisions that need to be made to design an experiment to ask the right questions. These decisions and how they translate to more insightful experiments is the subject of this panel discussion. Michael McCourt, Head of Engineering & Research at SigOpt, will facilitate a discussion that cuts across a variety of enterprise and university research applications to distill a set of foundational principles that can be universally applied to experiment design. This discussion will touch on how Paul Leu from the University of Pittsburgh applies multiobjective Bayesian optimization to run more efficient and insightful simulations for glass design. It will cover insights from Vishwanath Hegadekatte of Novelis on how enterprise constraints inform the way he structures experiments related to recycling processes. And it will include design decisions tha Marat Latypov makes to boost the efficiency of his research amidst resource constraints. Attendees will leave this panel with practical lessons they can apply in their own experimental design processes to drive more efficient, effective and scalable modeling.

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Add to Calendar 11/16/2021 2:00 pm 11/16/2021 2:45 pm America/Los_Angeles Panel: Best Practices for Experiment Design SigOpt AI & HPC Summit 2021 - Virtual & Free


Marat Latypov

Assistant Professor of Materials Science and Engineering, University of Arizona

Michael McCourt

Head of Engineering, SigOpt

Paul Leu

Associate Professor, University of Pittsburgh

Vishwanath Hegadekatte

Global R&D Manager, Novelis