Titan America’s parent company, TITAN Group, entered a strategic partnership with the Center for Information Technology Research in the Interest of Society and the Banatao Institute (CITRIS) at the University of California, Berkeley, aimed at accelerating the development of innovative digital solutions, using advanced research to explore new opportunities for the building materials industry.
The two partners will jointly pursue digital research initiatives designed to deliver prototypes with the potential to scale up and catalyze transformation across the industrial sector. The collaboration aims to generate new, publicly accessible knowledge that will benefit the broader research and innovation ecosystem, while having immediate applications in the building materials sector. By combining TITAN’s industry expertise with UC Berkeley’s world-class academic and research capabilities, the partnership creates a powerful bridge between academia and industry, fostering the development of cutting-edge digital solutions.
“At TITAN, we have always embraced experimentation in digital innovation, conceiving, piloting and implementing at scale digital solutions that revolutionize the way we produce and deliver our products. We believe strongly in the power of synergy to unlock opportunities, overcome barriers and drive progress, and we have a successful model of leveraging academic partnerships to that effect. Our partnership with UC Berkeley and CITRIS will equip us to push boundaries in AI technologies and pave new ground for both the industrial sector and the research ecosystem,” said TITAN Chief Digital and Strategy Officer Antonios Kyrkos.
The initial phase of the joint research effort, launched on Sept. 1, 2025, focuses on advancing digital twins for cement plants – an AI-powered technology that creates virtual models of processes, systems or entire plants, to simulate and optimize operations. The initial focus will be on developing optimization modules for specific parts of the cement manufacturing process, as well as solutions for enhancing the reliability of assets, using the most advanced data science techniques for AI algorithms and simulated models of end-to-end manufacturing processes.
