This AI reproducibility webinar series presented by FARR will kickoff with a focus on ML reproducibility. Dr. Odd Erik Gundersen and Kevin Coakley will highlight the sources that can lead to unintentional irreproducibility. In this webinar, you will learn valuable insights and practical ideas to help achieve reproducibility in machine learning research.  Additionally, you will gain a solid grasp of the common pitfalls that can undermine the reproducibility of your research. Join us on August 22nd at 8AM PT.  Register here!

Odd Erik Gundersen is an adjunct associate professor at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway, where he teaches courses and supervises master students in AI. He received his PhD from the Norwegian University of Science and Technology. Gundersen has applied AI in the industry, mostly for startups, since 2006. He has conducted several analyses of reproducibility in the artificial intelligence and machine learning literature, and has developed guidelines for reproducibility in data science.  Currently, he investigates how AI can be applied in the renewable energy sector and for driver training.

Kevin Coakley is a Senior Systems and Cloud Integration Engineer at the San Diego Supercomputer Center, UC San Diego where he supports the cloud infrastructure for multiple projects. Kevin’s research interest is in Computer Science where he focuses on reproducibility in Machine Learning.