TIME TO INNOVATE

Live Streamed Seminar

DOE and Bayesian Optimization for Faster, Smarter Experimentation

Date: 27 November 2025
Time: 11:00–12:00 CET | 10:00–11:00 GMT
Location: Online (Zoom)
Registration: Free

Stay ahead by solving problems faster, making better choices with less data, and speeding time to market.

When multiple inputs interact – making it unclear which ones matter – trial-and-error experimentation slows progress. Natural process variation adds noise, and too many runs fail to provide clear answers. In this webinar, discover how combining design of experiments (DOE) with Bayesian optimization helps you identify what works, faster.

If running a full DOE isn’t feasible given limited time, budget, or resource slimits, Bayesian optimization continues to move your data forward – enabling you to learn from every run and focus future tests on the most promising areas.

Learn how a machine learning-assisted approach can recommend the next best experiment based on your goals – enabling you to achieve better outcomes with fewer trials and less waste.

Register now to join us on Nov. 27 at 11 a.m. CET.

Key takeaways:

• How DOE and Bayesian optimization work together to accelerate R&D and manufacturing.

• Practical ways to save time, cut costs, and preserve resources while improving outcomes.

• How to decide what to test next with confidence, even in noisy environments.

• Examples from industry leaders showing proven, real-world impact.

What if I’m new to Bayesian optimization?
No prior experience is required. This webinar provides thorough explanations, peer insights, and short demos that are suitable for any skill level.

Can I ask questions during the session?
Yes. There will be a live Q&A at the end of the webinar.

Is there a cost to attend?
No. This webinar is free.

Can’t join us live? No problem! Register aniway and we will send the recording after the event.