SigOpt AI & HPC Summit, Nov 16 – Virtual and Free

Learn how PayPal, AWS, Intel, Accenture, MIT and Stanford apply experimentation to build better AI at the free SigOpt AI & HPC Summit.

Sponsored Post.


SigOpt is hosting our first user conference, the SigOpt AI & HPC Summit, on Tuesday, November 16, 2021. It is virtual and free to attend, so sign up today at

We decided to host the SigOpt Summit to showcase the great work of our customers. Our customers solve a wide variety of modeling problems and are deeply expert in these spaces. We think they have a lot to share and that many modelers could benefit from the lessons they’ve learned along the way. We are therefore hosting the Summit to serve as a platform for showcasing this great work and are grateful to do so.

So who are these customers and what will they discuss? Generally, each speaker will focus on modeling problems they have addressed with an emphasis on how experimentation was critical to this process. In particular, the Summit will focus on how they implemented best practice techniques and tools that enabled them to take an intelligent approach to their experimentation and therefore solve modeling problems more efficiently at greater scale and with better results. Here is a preview of some of the topics that we will cover during the event:

  • Shayan from Accenture will share how his team efficiently trained and deployed an ensemble of models to solve a predictive maintenance problem for their customer in the oil and gas space
  • Alexander from Stanford and Rafa from MIT will share different biological prediction problems they solved with deep learning and how hyperparameter optimization was critical to their workflow
  • Subutai from Numenta will discuss the application of sparsity and other neuroscientific techniques to evolving a novel architecture for ResNet on computer vision tasks to drive greater efficiency and robustness for performance
  • Venkatesh from PayPal will join Da from Amazon and Sasi from Intel Labs to discuss techniques for training and optimizing graph neural networks across massively parallel compute
  • Marat from the University of Arizona, Vishwanath from Novelis and Paul from the University of Pittsburgh will discuss how experimental design is critical driving breakthrough outcomes in their research related to physical processes

If you want to get a better sense of how SigOpt could impact your workflow than simply reading about use cases, sign up in seconds at If you want to learn from our customers, sign up for the SigOpt Summit for free at We look forward to seeing you there!