--- title: "Materials Informatics: Teaching and Research" description: Understand how to incorporate machine learning into your materials and chemicals teaching and research. image: https://info.citrine.io/hubfs/Teaching%20and%20Research.png --- [![](https://info.citrine.io/hs-fs/hubfs/Citrine_Full%20Logo_Pos.jpg?width=134&height=50&name=Citrine_Full%20Logo_Pos.jpg)](https://citrine.io?utm_source=landingpage&utm_medium=logo-header&utm_campaign=sustainability-webinar-032023) ### Webinar # Materials Informatics ### Teaching and Research with the Citrine Platform Dec 3rd 2026 8am PT / 11am ET / 5pm CET ### Register ## About the webinar Machine learning is becoming an important part of materials and chemicals development in industry, making it increasingly important in higher education and academic research. Students need practical experience using data and models to make informed experimental decisions. Researchers also need a straightforward, easy-to-use, chemically aware AI tool with a transparent workflow rather than a black-box approach. This webinar introduces the Citrine Platform, a no-code materials-informatics platform, alongside ready-made course materials and prepared datasets designed for hands-on undergraduate learning. We will show how students can prepare AI-ready data, review and adapt machine-learning models, craft search spaces, and select the next experiments to take to the lab. The session will share how the platform has been used in undergraduate teaching at California Polytechnic University, both in a standalone course and as a capstone design project option. We will also discuss grant-funded collaborative projects involving Citrine that bring universities, government laboratories, and industry together around important materials challenges. Finally, you will see how teaching with the Citrine Platform can also provide instructors with a practical way to upload, explore, and use their own research data. Join us to plan for the next semester. #### Feedback from Cal Poly student: - ###### "this makes me excited for my career" #### Feedback from educators that participated at a workshop at ASEE: - “The flow of the software was very interactive and is easy to implement for teaching.” - “Very useful for teaching. Will try and incorporate in my class.” Whether you teach undergraduates or want to empower your graduate students with AI, this session will equip you with practical tools to bring AI-driven materials informatics directly into your classroom and research. #### What You Will Learn: - How to guide students in building AI models, interpreting results, designing experiments, and selecting optimal candidates for the lab - See the Citrine Platform and understand how easy it is to create an AI model without writing a single line of code [Register](https://info.citrine.io/materials_informatics_at_university#register-now) #### Who Should Attend: - Lecturers teaching Materials 101, or AI for Materials - Heads of Department keen to incorporate AI in the curriculum - Materials researchers who want to understand how easy it can be to apply machine learning without coding.   ## Speakers ### James E. Saal Ph.D. Dr. James E. Saal is Vice President of External Research Programs at Citrine Informatics, where he leads government-funded research initiatives in materials informatics, data infrastructure, and AI-driven materials design. With over 15 years of experience spanning academia, national laboratories, and industry, he has pioneered the integration of machine learning, computational modeling, and experimental design to accelerate materials discovery. Dr. Saal has authored more than 80 peer-reviewed publications, holds multiple patents, and co-edited the book *Computational Materials System Design*. He is an active leader in the materials community, serving on the ASM International Board of Trustees and as Chair of the TMS Integrated Computational Materials Engineering Committee.  ![James shorter-1](https://info.citrine.io/hubfs/James%20shorter-1.jpg "James shorter-1") ### Michael Grijalva Michael Grijalva is a Business Development Representative at Citrine Informatics, where he works with industry and academic teams exploring AI for materials and chemicals development. In higher education, he works with faculty and university leaders to understand their teaching and research goals, identify funding and implementation needs, and connecting them with Citrine’s scientific and technical experts. Before joining Citrine, Michael worked at dotData, guiding organizations evaluating automated machine-learning solutions. A former teacher and coach, he brings an educator’s perspective and experience making technical concepts accessible to conversations about AI adoption in teaching and research. ![LinkedIn Photo](https://info.citrine.io/hs-fs/hubfs/LinkedIn%20Photo.jpg?width=412&height=391&name=LinkedIn%20Photo.jpg "LinkedIn Photo") ![Joel](https://info.citrine.io/hs-fs/hubfs/Joel.jpg?width=3&height=3&name=Joel.jpg "Joel") [Register](https://info.citrine.io/materials_informatics_at_university#register-now)