Webinars

Materials and Chemicals data is sparse. It is not “Big Data”. Which is why you need to use every bit of domain knowledge expert domain knowledge at your disposal to get value from AI in the materials and chemicals industry.

This webinar will share considerations for selecting and rolling out a Materials Informatics System (MIS) when investing in digitalization in materials and chemicals development.

Join Citrine, NIST, Cal Poly, Dow and MIT for a panel discussion about the use of AI for polymers.

Join Yoolhee Kim, data scientist at Citrine, as she shares lessons learned from our experience working with leading formulations companies.

Led by Jan Leuridan, SVP at Siemens Digital and Greg Mulholland, CEO at Citrine, this talk was recorded at Siemens Realize LIVE 2020.

Bryce Meredig joins MRS panel to discuss application of data science tools toward the design, understanding, and optimization of ceramic and glass materials.

Bryce Meredig (Chief Science Officer and Co-founder at Citrine) will demonstrate how Artificial Intelligence can accelerate materials development and enable data-driven decisions in materials and chemicals research and development.

Join us for a conversation between academia and industry about the future of work in the materials industry.

Learn how global leaders in specialty chemicals use the Citrine Platform to develop formulations that meet customer performance requirements with lower-cost ingredients, and adapt existing formulations when faced with supply chain disruptions.

In this webinar, we will discuss how materials informatics can improve return on investment in materials and chemicals R&D.

This discussion will help you prepare for a new informatics project by exploring how to build useful data sets, identify missing capabilities and communicate expectations.

Join Citrine Informatics as we go through a high-level overview of what sets AI for materials apart from other fields.

This discussion will feature examples of where digitalization and machine learning have had a short term impact for businesses facing such challenges.

This webinar will discuss domain-specific challenges that arise when applying ML to materials.

In this webinar you will learn about the four key pillars of data management in materials and chemistry: Structured, Standardized, Versioned, and Linked.

In this webinar, we’ll learn techniques for visualizing and assessing how R&D decisions affect tradeoffs in performance using machine learning models.

This webinar will be a brief introduction to key concepts and jargon in machine learning (ML).

The standard deviation is taught in every statistics class and supported in every statistics software package as a measure of distribution spread or “uncertainty”.

Come learn how Citrine thinks about materials data, and why a materials-centric data model is fundamental to scaling AI for your organization.

This webinar will use a recently completed successful project as a case study to illustrate how AI can guide R&D strategy in materials development.

This webinar will introduce natural language processing for materials science and highlight key tools & methods that you can leverage for your work.

This talk will cover the statistical fundamentals of machine learning model construction and evaluation, then show how those tools are applied for AI-guided experimentation.

This webinar will introduce basic concepts of neural networks and provide a survey of advanced deep learning methods & tools, and how you can leverage this for your work.